id sid tid token lemma pos bracis-28402 1 1 the the DET bracis-28402 1 2 effect effect NOUN bracis-28402 1 3 of of ADP bracis-28402 1 4     SPACE bracis-28402 1 5 statistical statistical ADJ bracis-28402 1 6 hypothesis hypothesis NOUN bracis-28402 1 7 testing testing NOUN bracis-28402 1 8 on on ADP bracis-28402 1 9     SPACE bracis-28402 1 10 machine machine NOUN bracis-28402 1 11 learning learning NOUN bracis-28402 1 12 model model NOUN bracis-28402 1 13 selection selection NOUN bracis-28402 1 14 | | NOUN bracis-28402 1 15 springer springer NOUN bracis-28402 1 16 nature nature PROPN bracis-28402 1 17 link link PROPN bracis-28402 1 18 ( ( PUNCT bracis-28402 1 19 formerly formerly ADV bracis-28402 1 20 springerlink springerlink NOUN bracis-28402 1 21 ) ) PUNCT bracis-28402 1 22 skip skip VERB bracis-28402 1 23 to to ADP bracis-28402 1 24 main main ADJ bracis-28402 1 25 content content NOUN bracis-28402 1 26 advertisement advertisement NOUN bracis-28402 1 27 log log NOUN bracis-28402 1 28 in in ADP bracis-28402 1 29 menu menu NOUN bracis-28402 1 30 find find VERB bracis-28402 1 31 a a DET bracis-28402 1 32 journal journal NOUN bracis-28402 1 33 publish publish VERB bracis-28402 1 34 with with ADP bracis-28402 1 35 us we PRON bracis-28402 1 36 track track VERB bracis-28402 1 37 your your PRON bracis-28402 1 38 research research NOUN bracis-28402 1 39 search search NOUN bracis-28402 1 40 cart cart NOUN bracis-28402 1 41 home home NOUN bracis-28402 1 42 intelligent intelligent ADJ bracis-28402 1 43 systems system NOUN bracis-28402 1 44 conference conference NOUN bracis-28402 1 45 paper paper NOUN bracis-28402 1 46 the the DET bracis-28402 1 47 effect effect NOUN bracis-28402 1 48 of of ADP bracis-28402 1 49     SPACE bracis-28402 1 50 statistical statistical ADJ bracis-28402 1 51 hypothesis hypothesis NOUN bracis-28402 1 52 testing testing NOUN bracis-28402 1 53 on on ADP bracis-28402 1 54     SPACE bracis-28402 1 55 machine machine NOUN bracis-28402 1 56 learning learning NOUN bracis-28402 1 57 model model NOUN bracis-28402 1 58 selection selection NOUN bracis-28402 1 59 conference conference NOUN bracis-28402 1 60 paper paper NOUN bracis-28402 1 61 first first ADV bracis-28402 1 62 online online ADV bracis-28402 1 63 : : PUNCT bracis-28402 1 64 12 12 NUM bracis-28402 1 65 october october NOUN bracis-28402 1 66 2023 2023 NUM bracis-28402 1 67 pp pp ADP bracis-28402 1 68 415–427 415–427 NUM bracis-28402 1 69 cite cite VERB bracis-28402 1 70 this this DET bracis-28402 1 71 conference conference NOUN bracis-28402 1 72 paper paper NOUN bracis-28402 1 73 access access NOUN bracis-28402 1 74 provided provide VERB bracis-28402 1 75 by by ADP bracis-28402 1 76 university university PROPN bracis-28402 1 77 of of ADP bracis-28402 1 78 notre notre PROPN bracis-28402 1 79 dame dame PROPN bracis-28402 1 80 hesburgh hesburgh PROPN bracis-28402 1 81 library library PROPN bracis-28402 1 82 download download PROPN bracis-28402 1 83 book book NOUN bracis-28402 1 84 pdf pdf PROPN bracis-28402 1 85 download download NOUN bracis-28402 1 86 book book NOUN bracis-28402 1 87 epub epub PROPN bracis-28402 1 88 intelligent intelligent ADJ bracis-28402 1 89 systems system NOUN bracis-28402 1 90 ( ( PUNCT bracis-28402 1 91 bracis bracis NOUN bracis-28402 1 92 2023 2023 NUM bracis-28402 1 93 ) ) PUNCT bracis-28402 1 94 the the DET bracis-28402 1 95 effect effect NOUN bracis-28402 1 96 of of ADP bracis-28402 1 97     SPACE bracis-28402 1 98 statistical statistical ADJ bracis-28402 1 99 hypothesis hypothesis NOUN bracis-28402 1 100 testing testing NOUN bracis-28402 1 101 on on ADP bracis-28402 1 102     SPACE bracis-28402 1 103 machine machine NOUN bracis-28402 1 104 learning learning NOUN bracis-28402 1 105 model model NOUN bracis-28402 1 106 selection selection NOUN bracis-28402 1 107 download download NOUN bracis-28402 1 108 book book NOUN bracis-28402 1 109 pdf pdf PROPN bracis-28402 1 110 download download NOUN bracis-28402 1 111 book book PROPN bracis-28402 1 112 epub epub PROPN bracis-28402 1 113 marcel marcel PROPN bracis-28402 1 114 chacon chacon PROPN bracis-28402 1 115 gonçalves9 gonçalves9 PROPN bracis-28402 1 116 & & CCONJ bracis-28402 1 117 rodrigo rodrigo PROPN bracis-28402 1 118 silva silva PROPN bracis-28402 1 119     SPACE bracis-28402 1 120 orcid orcid NOUN bracis-28402 1 121 : : PUNCT bracis-28402 1 122 orcid.org/0000-0003-2547-383510 orcid.org/0000-0003-2547-383510 VERB bracis-28402 1 123     SPACE bracis-28402 1 124 part part NOUN bracis-28402 1 125 of of ADP bracis-28402 1 126 the the DET bracis-28402 1 127 book book NOUN bracis-28402 1 128 series series NOUN bracis-28402 1 129 : : PUNCT bracis-28402 1 130 lecture lecture NOUN bracis-28402 1 131 notes note NOUN bracis-28402 1 132 in in ADP bracis-28402 1 133 computer computer NOUN bracis-28402 1 134 science science NOUN bracis-28402 1 135 ( ( PUNCT bracis-28402 1 136 ( ( PUNCT bracis-28402 1 137 lnai lnai ADJ bracis-28402 1 138 , , PUNCT bracis-28402 1 139 volume volume NOUN bracis-28402 1 140 14196 14196 NUM bracis-28402 1 141 ) ) PUNCT bracis-28402 1 142 ) ) PUNCT bracis-28402 1 143 included include VERB bracis-28402 1 144 in in ADP bracis-28402 1 145 the the DET bracis-28402 1 146 following follow VERB bracis-28402 1 147 conference conference NOUN bracis-28402 1 148 series series NOUN bracis-28402 1 149 : : PUNCT bracis-28402 1 150 brazilian brazilian ADJ bracis-28402 1 151 conference conference NOUN bracis-28402 1 152 on on ADP bracis-28402 1 153 intelligent intelligent ADJ bracis-28402 1 154 systems system NOUN bracis-28402 1 155 643 643 NUM bracis-28402 1 156 accesses access VERB bracis-28402 1 157 4 4 NUM bracis-28402 1 158 citations citation NOUN bracis-28402 1 159 abstract abstract ADJ bracis-28402 1 160 statistical statistical ADJ bracis-28402 1 161 tests test NOUN bracis-28402 1 162 of of ADP bracis-28402 1 163 hypothesis hypothesis NOUN bracis-28402 1 164 play play VERB bracis-28402 1 165 a a DET bracis-28402 1 166 crucial crucial ADJ bracis-28402 1 167 role role NOUN bracis-28402 1 168 in in ADP bracis-28402 1 169 evaluating evaluate VERB bracis-28402 1 170 the the DET bracis-28402 1 171 performance performance NOUN bracis-28402 1 172 of of ADP bracis-28402 1 173 machine machine NOUN bracis-28402 1 174 learning learning NOUN bracis-28402 1 175 ( ( PUNCT bracis-28402 1 176 ml ml NOUN bracis-28402 1 177 ) ) PUNCT bracis-28402 1 178 models model NOUN bracis-28402 1 179 and and CCONJ bracis-28402 1 180 selecting select VERB bracis-28402 1 181 the the DET bracis-28402 1 182 best good ADJ bracis-28402 1 183 model model NOUN bracis-28402 1 184 among among ADP bracis-28402 1 185 a a DET bracis-28402 1 186 set set NOUN bracis-28402 1 187 of of ADP bracis-28402 1 188 candidates candidate NOUN bracis-28402 1 189 . . PUNCT bracis-28402 2 1 however however ADV bracis-28402 2 2 , , PUNCT bracis-28402 2 3 their their PRON bracis-28402 2 4 effectiveness effectiveness NOUN bracis-28402 2 5 in in ADP bracis-28402 2 6 selecting selecting NOUN bracis-28402 2 7 models model NOUN bracis-28402 2 8 over over ADP bracis-28402 2 9 larger large ADJ bracis-28402 2 10 periods period NOUN bracis-28402 2 11 of of ADP bracis-28402 2 12 time time NOUN bracis-28402 2 13 remains remain VERB bracis-28402 2 14 unclear unclear ADJ bracis-28402 2 15 . . PUNCT bracis-28402 3 1 this this DET bracis-28402 3 2 study study NOUN bracis-28402 3 3 aims aim VERB bracis-28402 3 4 to to PART bracis-28402 3 5 investigate investigate VERB bracis-28402 3 6 the the DET bracis-28402 3 7 impact impact NOUN bracis-28402 3 8 of of ADP bracis-28402 3 9 statistical statistical ADJ bracis-28402 3 10 tests test NOUN bracis-28402 3 11 on on ADP bracis-28402 3 12 ml ml NOUN bracis-28402 3 13 model model NOUN bracis-28402 3 14 selection selection NOUN bracis-28402 3 15 in in ADP bracis-28402 3 16 sequential sequential ADJ bracis-28402 3 17 experiments experiment NOUN bracis-28402 3 18 . . PUNCT bracis-28402 4 1 specifically specifically ADV bracis-28402 4 2 , , PUNCT bracis-28402 4 3 we we PRON bracis-28402 4 4 examine examine VERB bracis-28402 4 5 whether whether SCONJ bracis-28402 4 6 selecting select VERB bracis-28402 4 7 models model NOUN bracis-28402 4 8 based base VERB bracis-28402 4 9 on on ADP bracis-28402 4 10 statistical statistical ADJ bracis-28402 4 11 tests test NOUN bracis-28402 4 12 leads lead VERB bracis-28402 4 13 to to ADP bracis-28402 4 14 higher high ADJ bracis-28402 4 15 quality quality NOUN bracis-28402 4 16 models model NOUN bracis-28402 4 17 after after ADP bracis-28402 4 18 a a DET bracis-28402 4 19 significant significant ADJ bracis-28402 4 20 number number NOUN bracis-28402 4 21 of of ADP bracis-28402 4 22 iterations iteration NOUN bracis-28402 4 23 and and CCONJ bracis-28402 4 24 explore explore VERB bracis-28402 4 25 the the DET bracis-28402 4 26 effect effect NOUN bracis-28402 4 27 of of ADP bracis-28402 4 28 the the DET bracis-28402 4 29 number number NOUN bracis-28402 4 30 of of ADP bracis-28402 4 31 tests test NOUN bracis-28402 4 32 performed perform VERB bracis-28402 4 33 and and CCONJ bracis-28402 4 34 the the DET bracis-28402 4 35 preferred preferred ADJ bracis-28402 4 36 statistical statistical ADJ bracis-28402 4 37 test test NOUN bracis-28402 4 38 for for ADP bracis-28402 4 39 different different ADJ bracis-28402 4 40 experimental experimental ADJ bracis-28402 4 41 time time NOUN bracis-28402 4 42 horizons horizon NOUN bracis-28402 4 43 . . PUNCT bracis-28402 5 1 the the DET bracis-28402 5 2 study study NOUN bracis-28402 5 3 on on ADP bracis-28402 5 4 binary binary ADJ bracis-28402 5 5 classification classification NOUN bracis-28402 5 6 problems problem NOUN bracis-28402 5 7 reveals reveal VERB bracis-28402 5 8 that that SCONJ bracis-28402 5 9 the the DET bracis-28402 5 10 use use NOUN bracis-28402 5 11 of of ADP bracis-28402 5 12 statistical statistical ADJ bracis-28402 5 13 tests test NOUN bracis-28402 5 14 should should AUX bracis-28402 5 15 be be AUX bracis-28402 5 16 approached approach VERB bracis-28402 5 17 with with ADP bracis-28402 5 18 caution caution NOUN bracis-28402 5 19 , , PUNCT bracis-28402 5 20 particularly particularly ADV bracis-28402 5 21 in in ADP bracis-28402 5 22 challenging challenge VERB bracis-28402 5 23 scenarios scenario NOUN bracis-28402 5 24 where where SCONJ bracis-28402 5 25 generating generate VERB bracis-28402 5 26 improved improved ADJ bracis-28402 5 27 models model NOUN bracis-28402 5 28 is be AUX bracis-28402 5 29 difficult difficult ADJ bracis-28402 5 30 . . PUNCT bracis-28402 6 1 the the DET bracis-28402 6 2 analysis analysis NOUN bracis-28402 6 3 demonstrates demonstrate VERB bracis-28402 6 4 that that SCONJ bracis-28402 6 5 statistical statistical ADJ bracis-28402 6 6 tests test NOUN bracis-28402 6 7 may may AUX bracis-28402 6 8 impede impede VERB bracis-28402 6 9 progress progress NOUN bracis-28402 6 10 and and CCONJ bracis-28402 6 11 impose impose VERB bracis-28402 6 12 overly overly ADV bracis-28402 6 13 stringent stringent ADJ bracis-28402 6 14 acceptance acceptance NOUN bracis-28402 6 15 criteria criterion NOUN bracis-28402 6 16 for for ADP bracis-28402 6 17 new new ADJ bracis-28402 6 18 models model NOUN bracis-28402 6 19 , , PUNCT bracis-28402 6 20 hindering hinder VERB bracis-28402 6 21 the the DET bracis-28402 6 22 selection selection NOUN bracis-28402 6 23 of of ADP bracis-28402 6 24 high high ADJ bracis-28402 6 25 - - PUNCT bracis-28402 6 26 quality quality NOUN bracis-28402 6 27 models model NOUN bracis-28402 6 28 . . PUNCT bracis-28402 7 1 the the DET bracis-28402 7 2 findings finding NOUN bracis-28402 7 3 also also ADV bracis-28402 7 4 indicate indicate VERB bracis-28402 7 5 that that SCONJ bracis-28402 7 6 the the DET bracis-28402 7 7 dominance dominance NOUN bracis-28402 7 8 of of ADP bracis-28402 7 9 versions version NOUN bracis-28402 7 10 without without ADP bracis-28402 7 11 statistical statistical ADJ bracis-28402 7 12 tests test NOUN bracis-28402 7 13 remained remain VERB bracis-28402 7 14 consistent consistent ADJ bracis-28402 7 15 , , PUNCT bracis-28402 7 16 suggesting suggest VERB bracis-28402 7 17 the the DET bracis-28402 7 18 need need NOUN bracis-28402 7 19 for for ADP bracis-28402 7 20 further further ADJ bracis-28402 7 21 research research NOUN bracis-28402 7 22 in in ADP bracis-28402 7 23 this this DET bracis-28402 7 24 area area NOUN bracis-28402 7 25 . . PUNCT bracis-28402 8 1 although although SCONJ bracis-28402 8 2 this this DET bracis-28402 8 3 study study NOUN bracis-28402 8 4 is be AUX bracis-28402 8 5 limited limit VERB bracis-28402 8 6 by by ADP bracis-28402 8 7 the the DET bracis-28402 8 8 number number NOUN bracis-28402 8 9 of of ADP bracis-28402 8 10 datasets dataset NOUN bracis-28402 8 11 and and CCONJ bracis-28402 8 12 the the DET bracis-28402 8 13 absence absence NOUN bracis-28402 8 14 of of ADP bracis-28402 8 15 pre pre ADJ bracis-28402 8 16 - - ADJ bracis-28402 8 17 test test ADJ bracis-28402 8 18 assumption assumption NOUN bracis-28402 8 19 verification verification NOUN bracis-28402 8 20 , , PUNCT bracis-28402 8 21 it it PRON bracis-28402 8 22 emphasizes emphasize VERB bracis-28402 8 23 the the DET bracis-28402 8 24 importance importance NOUN bracis-28402 8 25 of of ADP bracis-28402 8 26 understanding understand VERB bracis-28402 8 27 the the DET bracis-28402 8 28 impact impact NOUN bracis-28402 8 29 of of ADP bracis-28402 8 30 statistical statistical ADJ bracis-28402 8 31 tests test NOUN bracis-28402 8 32 on on ADP bracis-28402 8 33 ml ml NOUN bracis-28402 8 34 model model NOUN bracis-28402 8 35 selection selection NOUN bracis-28402 8 36 . . PUNCT bracis-28402 9 1 access access NOUN bracis-28402 9 2 provided provide VERB bracis-28402 9 3 by by ADP bracis-28402 9 4 university university PROPN bracis-28402 9 5 of of ADP bracis-28402 9 6 notre notre PROPN bracis-28402 9 7 dame dame PROPN bracis-28402 9 8 hesburgh hesburgh PROPN bracis-28402 9 9 library library PROPN bracis-28402 9 10 . . PUNCT bracis-28402 10 1 download download PROPN bracis-28402 10 2 conference conference NOUN bracis-28402 10 3 paper paper NOUN bracis-28402 10 4 pdf pdf NOUN bracis-28402 10 5 similar similar ADJ bracis-28402 10 6 content content NOUN bracis-28402 10 7 being be AUX bracis-28402 10 8 viewed view VERB bracis-28402 10 9 by by ADP bracis-28402 10 10 others other NOUN bracis-28402 10 11 quality quality NOUN bracis-28402 10 12 assurance assurance NOUN bracis-28402 10 13 strategies strategy NOUN bracis-28402 10 14 for for ADP bracis-28402 10 15 machine machine NOUN bracis-28402 10 16 learning learning NOUN bracis-28402 10 17 applications application NOUN bracis-28402 10 18 in in ADP bracis-28402 10 19 big big ADJ bracis-28402 10 20 data datum NOUN bracis-28402 10 21 analytics analytic NOUN bracis-28402 10 22 : : PUNCT bracis-28402 10 23 an an DET bracis-28402 10 24 overview overview NOUN bracis-28402 10 25 article article NOUN bracis-28402 10 26 open open ADJ bracis-28402 10 27 access access NOUN bracis-28402 10 28 30 30 NUM bracis-28402 10 29 october october NOUN bracis-28402 10 30 2024 2024 NUM bracis-28402 10 31 model model NOUN bracis-28402 10 32 selection selection NOUN bracis-28402 10 33 chapter chapter NOUN bracis-28402 10 34 © © PROPN bracis-28402 10 35 2018 2018 NUM bracis-28402 10 36 logic logic NOUN bracis-28402 10 37 - - PUNCT bracis-28402 10 38 based base VERB bracis-28402 10 39 explainability explainability NOUN bracis-28402 10 40 in in ADP bracis-28402 10 41     SPACE bracis-28402 10 42 machine machine NOUN bracis-28402 10 43 learning learn VERB bracis-28402 10 44 chapter chapter NOUN bracis-28402 10 45 © © PROPN bracis-28402 10 46 2023 2023 NUM bracis-28402 10 47 explore explore VERB bracis-28402 10 48 related relate VERB bracis-28402 10 49 subjects subject NOUN bracis-28402 10 50 discover discover VERB bracis-28402 10 51 the the DET bracis-28402 10 52 latest late ADJ bracis-28402 10 53 articles article NOUN bracis-28402 10 54 , , PUNCT bracis-28402 10 55 books book NOUN bracis-28402 10 56 and and CCONJ bracis-28402 10 57 news news NOUN bracis-28402 10 58 in in ADP bracis-28402 10 59 related related ADJ bracis-28402 10 60 subjects subject NOUN bracis-28402 10 61 , , PUNCT bracis-28402 10 62 suggested suggest VERB bracis-28402 10 63 using use VERB bracis-28402 10 64 machine machine NOUN bracis-28402 10 65 learning learning NOUN bracis-28402 10 66 . . PUNCT bracis-28402 11 1 biostatistics biostatistic NOUN bracis-28402 11 2 linear linear PROPN bracis-28402 11 3 models model NOUN bracis-28402 11 4 and and CCONJ bracis-28402 11 5 regression regression NOUN bracis-28402 11 6 machine machine NOUN bracis-28402 11 7 learning learning NOUN bracis-28402 11 8 model model NOUN bracis-28402 11 9 theory theory NOUN bracis-28402 11 10 statistical statistical ADJ bracis-28402 11 11 learning learn VERB bracis-28402 11 12 statistical statistical ADJ bracis-28402 11 13 theory theory NOUN bracis-28402 11 14 and and CCONJ bracis-28402 11 15 methods method NOUN bracis-28402 11 16 1 1 NUM bracis-28402 11 17 introduction introduction NOUN bracis-28402 11 18 in in ADP bracis-28402 11 19 recent recent ADJ bracis-28402 11 20 years year NOUN bracis-28402 11 21 , , PUNCT bracis-28402 11 22 machine machine NOUN bracis-28402 11 23 learning learning NOUN bracis-28402 11 24 ( ( PUNCT bracis-28402 11 25 ml ml NOUN bracis-28402 11 26 ) ) PUNCT bracis-28402 11 27 has have AUX bracis-28402 11 28 become become VERB bracis-28402 11 29 a a DET bracis-28402 11 30 popular popular ADJ bracis-28402 11 31 tool tool NOUN bracis-28402 11 32 for for ADP bracis-28402 11 33 data datum NOUN bracis-28402 11 34 analysis analysis NOUN bracis-28402 11 35 in in ADP bracis-28402 11 36 various various ADJ bracis-28402 11 37 fields field NOUN bracis-28402 11 38 such such ADJ bracis-28402 11 39 as as ADP bracis-28402 11 40 finance finance NOUN bracis-28402 11 41 [ [ X bracis-28402 11 42 1 1 NUM bracis-28402 11 43 ] ] PUNCT bracis-28402 11 44 , , PUNCT bracis-28402 11 45 healthcare healthcare PROPN bracis-28402 12 1 [ [ X bracis-28402 12 2 2 2 NUM bracis-28402 12 3 ] ] PUNCT bracis-28402 12 4 , , PUNCT bracis-28402 12 5 and and CCONJ bracis-28402 12 6 marketing marketing NOUN bracis-28402 12 7 [ [ X bracis-28402 12 8 8 8 NUM bracis-28402 12 9 ] ] PUNCT bracis-28402 12 10 . . PUNCT bracis-28402 13 1 the the DET bracis-28402 13 2 ultimate ultimate ADJ bracis-28402 13 3 goal goal NOUN bracis-28402 13 4 of of ADP bracis-28402 13 5 machine machine NOUN bracis-28402 13 6 learning learning NOUN bracis-28402 13 7 is be AUX bracis-28402 13 8 to to PART bracis-28402 13 9 build build VERB bracis-28402 13 10 predictive predictive ADJ bracis-28402 13 11 models model NOUN bracis-28402 13 12 that that PRON bracis-28402 13 13 can can AUX bracis-28402 13 14 accurately accurately ADV bracis-28402 13 15 predict predict VERB bracis-28402 13 16 the the DET bracis-28402 13 17 target target NOUN bracis-28402 13 18 variable variable NOUN bracis-28402 13 19 based base VERB bracis-28402 13 20 on on ADP bracis-28402 13 21 the the DET bracis-28402 13 22 input input NOUN bracis-28402 13 23 features feature NOUN bracis-28402 13 24 . . PUNCT bracis-28402 14 1 choosing choose VERB bracis-28402 14 2 the the DET bracis-28402 14 3 best good ADJ bracis-28402 14 4 model model NOUN bracis-28402 14 5 among among ADP bracis-28402 14 6 a a DET bracis-28402 14 7 set set NOUN bracis-28402 14 8 of of ADP bracis-28402 14 9 candidate candidate NOUN bracis-28402 14 10 models model NOUN bracis-28402 14 11 , , PUNCT bracis-28402 14 12 however however ADV bracis-28402 14 13 , , PUNCT bracis-28402 14 14 can can AUX bracis-28402 14 15 be be AUX bracis-28402 14 16 a a DET bracis-28402 14 17 daunting daunting ADJ bracis-28402 14 18 task task NOUN bracis-28402 14 19 . . PUNCT bracis-28402 15 1 one one NUM bracis-28402 15 2 approach approach NOUN bracis-28402 15 3 is be AUX bracis-28402 15 4 to to PART bracis-28402 15 5 use use VERB bracis-28402 15 6 statistical statistical ADJ bracis-28402 15 7 tests test NOUN bracis-28402 15 8 of of ADP bracis-28402 15 9 hypothesis hypothesis NOUN bracis-28402 15 10 to to PART bracis-28402 15 11 compare compare VERB bracis-28402 15 12 the the DET bracis-28402 15 13 performance performance NOUN bracis-28402 15 14 of of ADP bracis-28402 15 15 different different ADJ bracis-28402 15 16 models model NOUN bracis-28402 15 17 [ [ X bracis-28402 15 18 4 4 NUM bracis-28402 15 19 ] ] PUNCT bracis-28402 15 20 . . PUNCT bracis-28402 16 1 the the DET bracis-28402 16 2 statistical statistical ADJ bracis-28402 16 3 tests test NOUN bracis-28402 16 4 of of ADP bracis-28402 16 5 hypothesis hypothesis NOUN bracis-28402 16 6 are be AUX bracis-28402 16 7 widely widely ADV bracis-28402 16 8 used use VERB bracis-28402 16 9 in in ADP bracis-28402 16 10 the the DET bracis-28402 16 11 scientific scientific ADJ bracis-28402 16 12 community community NOUN bracis-28402 16 13 to to PART bracis-28402 16 14 evaluate evaluate VERB bracis-28402 16 15 the the DET bracis-28402 16 16 significance significance NOUN bracis-28402 16 17 of of ADP bracis-28402 16 18 a a DET bracis-28402 16 19 result result NOUN bracis-28402 16 20 or or CCONJ bracis-28402 16 21 to to PART bracis-28402 16 22 compare compare VERB bracis-28402 16 23 the the DET bracis-28402 16 24 performance performance NOUN bracis-28402 16 25 of of ADP bracis-28402 16 26 different different ADJ bracis-28402 16 27 methods method NOUN bracis-28402 16 28 [ [ X bracis-28402 16 29 7 7 NUM bracis-28402 16 30 ] ] PUNCT bracis-28402 16 31 . . PUNCT bracis-28402 17 1 in in ADP bracis-28402 17 2 machine machine NOUN bracis-28402 17 3 learning learning NOUN bracis-28402 17 4 , , PUNCT bracis-28402 17 5 statistical statistical ADJ bracis-28402 17 6 tests test NOUN bracis-28402 17 7 are be AUX bracis-28402 17 8 used use VERB bracis-28402 17 9 to to PART bracis-28402 17 10 determine determine VERB bracis-28402 17 11 whether whether SCONJ bracis-28402 17 12 there there PRON bracis-28402 17 13 is be VERB bracis-28402 17 14 a a DET bracis-28402 17 15 significant significant ADJ bracis-28402 17 16 difference difference NOUN bracis-28402 17 17 between between ADP bracis-28402 17 18 the the DET bracis-28402 17 19 performance performance NOUN bracis-28402 17 20 of of ADP bracis-28402 17 21 two two NUM bracis-28402 17 22 or or CCONJ bracis-28402 17 23 more more ADJ bracis-28402 17 24 models model NOUN bracis-28402 17 25 . . PUNCT bracis-28402 18 1 the the DET bracis-28402 18 2 use use NOUN bracis-28402 18 3 of of ADP bracis-28402 18 4 statistical statistical ADJ bracis-28402 18 5 tests test NOUN bracis-28402 18 6 in in ADP bracis-28402 18 7 ml ml NOUN bracis-28402 18 8 model model NOUN bracis-28402 18 9 selection selection NOUN bracis-28402 18 10 has have AUX bracis-28402 18 11 become become VERB bracis-28402 18 12 an an DET bracis-28402 18 13 important important ADJ bracis-28402 18 14 topic topic NOUN bracis-28402 18 15 of of ADP bracis-28402 18 16 research research NOUN bracis-28402 18 17 due due ADP bracis-28402 18 18 to to ADP bracis-28402 18 19 its its PRON bracis-28402 18 20 impact impact NOUN bracis-28402 18 21 on on ADP bracis-28402 18 22 the the DET bracis-28402 18 23 performance performance NOUN bracis-28402 18 24 of of ADP bracis-28402 18 25 the the DET bracis-28402 18 26 final final ADJ bracis-28402 18 27 model model NOUN bracis-28402 18 28 [ [ X bracis-28402 18 29 3,4,5 3,4,5 NUM bracis-28402 18 30 , , PUNCT bracis-28402 18 31 14 14 NUM bracis-28402 18 32 , , PUNCT bracis-28402 18 33 17 17 NUM bracis-28402 18 34 ] ] PUNCT bracis-28402 18 35 . . PUNCT bracis-28402 19 1 the the DET bracis-28402 19 2 use use NOUN bracis-28402 19 3 bayesian bayesian NOUN bracis-28402 19 4 statistics statistic NOUN bracis-28402 19 5 is be AUX bracis-28402 19 6 studied study VERB bracis-28402 19 7 in in ADP bracis-28402 19 8 [ [ X bracis-28402 19 9 3 3 NUM bracis-28402 19 10 , , PUNCT bracis-28402 19 11 5 5 NUM bracis-28402 19 12 ] ] PUNCT bracis-28402 19 13 while while SCONJ bracis-28402 19 14 the the DET bracis-28402 19 15 use use NOUN bracis-28402 19 16 of of ADP bracis-28402 19 17 frequentist frequentist NOUN bracis-28402 19 18 tests test NOUN bracis-28402 19 19 is be AUX bracis-28402 19 20 the the DET bracis-28402 19 21 focus focus NOUN bracis-28402 19 22 of of ADP bracis-28402 19 23 [ [ X bracis-28402 19 24 4 4 NUM bracis-28402 19 25 , , PUNCT bracis-28402 19 26 14 14 NUM bracis-28402 19 27 , , PUNCT bracis-28402 19 28 17 17 NUM bracis-28402 19 29 ] ] PUNCT bracis-28402 19 30 . . PUNCT bracis-28402 20 1 while while SCONJ bracis-28402 20 2 these these DET bracis-28402 20 3 studies study NOUN bracis-28402 20 4 investigate investigate VERB bracis-28402 20 5 the the DET bracis-28402 20 6 ability ability NOUN bracis-28402 20 7 of of ADP bracis-28402 20 8 statistical statistical ADJ bracis-28402 20 9 tests test NOUN bracis-28402 20 10 to to PART bracis-28402 20 11 choose choose VERB bracis-28402 20 12 the the DET bracis-28402 20 13 best good ADJ bracis-28402 20 14 model model NOUN bracis-28402 20 15 in in ADP bracis-28402 20 16 a a DET bracis-28402 20 17 single single ADJ bracis-28402 20 18 experiment experiment NOUN bracis-28402 20 19 , , PUNCT bracis-28402 20 20 this this DET bracis-28402 20 21 study study NOUN bracis-28402 20 22 aims aim VERB bracis-28402 20 23 to to PART bracis-28402 20 24 understand understand VERB bracis-28402 20 25 their their PRON bracis-28402 20 26 effectiveness effectiveness NOUN bracis-28402 20 27 when when SCONJ bracis-28402 20 28 they they PRON bracis-28402 20 29 are be AUX bracis-28402 20 30 applied apply VERB bracis-28402 20 31 over over ADP bracis-28402 20 32 larger large ADJ bracis-28402 20 33 periods period NOUN bracis-28402 20 34 of of ADP bracis-28402 20 35 time time NOUN bracis-28402 20 36 . . PUNCT bracis-28402 21 1 more more ADV bracis-28402 21 2 specifically specifically ADV bracis-28402 21 3 , , PUNCT bracis-28402 21 4 this this DET bracis-28402 21 5 study study NOUN bracis-28402 21 6 investigates investigate VERB bracis-28402 21 7 whether whether SCONJ bracis-28402 21 8 the the DET bracis-28402 21 9 statistical statistical ADJ bracis-28402 21 10 tests test NOUN bracis-28402 21 11 commonly commonly ADV bracis-28402 21 12 used use VERB bracis-28402 21 13 for for ADP bracis-28402 21 14 selecting select VERB bracis-28402 21 15 the the DET bracis-28402 21 16 best good ADJ bracis-28402 21 17 ml ml NOUN bracis-28402 21 18 model model NOUN bracis-28402 21 19 in in ADP bracis-28402 21 20 a a DET bracis-28402 21 21 single single ADJ bracis-28402 21 22 experiment experiment NOUN bracis-28402 21 23 remain remain VERB bracis-28402 21 24 effective effective ADJ bracis-28402 21 25 when when SCONJ bracis-28402 21 26 applied apply VERB bracis-28402 21 27 in in ADP bracis-28402 21 28 sequences sequence NOUN bracis-28402 21 29 of of ADP bracis-28402 21 30 experiments experiment NOUN bracis-28402 21 31 . . PUNCT bracis-28402 22 1 to to PART bracis-28402 22 2 achieve achieve VERB bracis-28402 22 3 this this PRON bracis-28402 22 4 , , PUNCT bracis-28402 22 5 using use VERB bracis-28402 22 6 a a DET bracis-28402 22 7 set set NOUN bracis-28402 22 8 a a DET bracis-28402 22 9 binary binary ADJ bracis-28402 22 10 classification classification NOUN bracis-28402 22 11 problems problem NOUN bracis-28402 22 12 , , PUNCT bracis-28402 22 13 the the DET bracis-28402 22 14 quality quality NOUN bracis-28402 22 15 of of ADP bracis-28402 22 16 the the DET bracis-28402 22 17 models model NOUN bracis-28402 22 18 selected select VERB bracis-28402 22 19 by by ADP bracis-28402 22 20 each each DET bracis-28402 22 21 test test NOUN bracis-28402 22 22 is be AUX bracis-28402 22 23 examined examine VERB bracis-28402 22 24 after after ADP bracis-28402 22 25 a a DET bracis-28402 22 26 significant significant ADJ bracis-28402 22 27 number number NOUN bracis-28402 22 28 of of ADP bracis-28402 22 29 iterations iteration NOUN bracis-28402 22 30 . . PUNCT bracis-28402 23 1 other other ADJ bracis-28402 23 2 parameters parameter NOUN bracis-28402 23 3 such such ADJ bracis-28402 23 4 as as ADP bracis-28402 23 5 the the DET bracis-28402 23 6 number number NOUN bracis-28402 23 7 of of ADP bracis-28402 23 8 iterations iteration NOUN bracis-28402 23 9 and and CCONJ bracis-28402 23 10 the the DET bracis-28402 23 11 amount amount NOUN bracis-28402 23 12 of of ADP bracis-28402 23 13 data datum NOUN bracis-28402 23 14 collected collect VERB bracis-28402 23 15 to to PART bracis-28402 23 16 feed feed VERB bracis-28402 23 17 the the DET bracis-28402 23 18 statistical statistical ADJ bracis-28402 23 19 tests test NOUN bracis-28402 23 20 are be AUX bracis-28402 23 21 also also ADV bracis-28402 23 22 investigated investigate VERB bracis-28402 23 23 . . PUNCT bracis-28402 24 1 in in ADP bracis-28402 24 2 this this DET bracis-28402 24 3 context context NOUN bracis-28402 24 4 , , PUNCT bracis-28402 24 5 the the DET bracis-28402 24 6 research research NOUN bracis-28402 24 7 questions question NOUN bracis-28402 24 8 investigated investigate VERB bracis-28402 24 9 in in ADP bracis-28402 24 10 this this DET bracis-28402 24 11 study study NOUN bracis-28402 24 12 can can AUX bracis-28402 24 13 be be AUX bracis-28402 24 14 laid lay VERB bracis-28402 24 15 down down ADP bracis-28402 24 16 as as SCONJ bracis-28402 24 17 follows follow VERB bracis-28402 24 18 : : PUNCT bracis-28402 25 1 1 1 X bracis-28402 25 2 . . PUNCT bracis-28402 25 3 the the DET bracis-28402 25 4 selection selection NOUN bracis-28402 25 5 of of ADP bracis-28402 25 6 machine machine NOUN bracis-28402 25 7 learning learning NOUN bracis-28402 25 8 models model NOUN bracis-28402 25 9 based base VERB bracis-28402 25 10 on on ADP bracis-28402 25 11 statistical statistical ADJ bracis-28402 25 12 tests test NOUN bracis-28402 25 13 of of ADP bracis-28402 25 14 hypothesis hypothesis NOUN bracis-28402 25 15 lead lead NOUN bracis-28402 25 16 to to ADP bracis-28402 25 17 higher high ADJ bracis-28402 25 18 quality quality NOUN bracis-28402 25 19 models model NOUN bracis-28402 25 20 after after ADP bracis-28402 25 21 a a DET bracis-28402 25 22 large large ADJ bracis-28402 25 23 number number NOUN bracis-28402 25 24 of of ADP bracis-28402 25 25 iterations iteration NOUN bracis-28402 25 26 ? ? PUNCT bracis-28402 26 1 2 2 X bracis-28402 26 2 . . X bracis-28402 26 3 what what PRON bracis-28402 26 4 is be AUX bracis-28402 26 5 the the DET bracis-28402 26 6 effect effect NOUN bracis-28402 26 7 of of ADP bracis-28402 26 8 the the DET bracis-28402 26 9 number number NOUN bracis-28402 26 10 of of ADP bracis-28402 26 11 tests test NOUN bracis-28402 26 12 performed perform VERB bracis-28402 26 13 to to PART bracis-28402 26 14 acquire acquire VERB bracis-28402 26 15 data datum NOUN bracis-28402 26 16 to to ADP bracis-28402 26 17 these these DET bracis-28402 26 18 statistical statistical ADJ bracis-28402 26 19 test test NOUN bracis-28402 26 20 of of ADP bracis-28402 26 21 hypothesis hypothesis NOUN bracis-28402 26 22 ? ? PUNCT bracis-28402 27 1 3 3 X bracis-28402 27 2 . . X bracis-28402 27 3 is be AUX bracis-28402 27 4 there there PRON bracis-28402 27 5 a a DET bracis-28402 27 6 preferred preferred ADJ bracis-28402 27 7 statistical statistical ADJ bracis-28402 27 8 test test NOUN bracis-28402 27 9 for for ADP bracis-28402 27 10 different different ADJ bracis-28402 27 11 experimental experimental ADJ bracis-28402 27 12 time time NOUN bracis-28402 27 13 horizons horizon NOUN bracis-28402 27 14 ? ? PUNCT bracis-28402 28 1 the the DET bracis-28402 28 2 rest rest NOUN bracis-28402 28 3 of of ADP bracis-28402 28 4 the the DET bracis-28402 28 5 paper paper NOUN bracis-28402 28 6 is be AUX bracis-28402 28 7 organized organize VERB bracis-28402 28 8 as as SCONJ bracis-28402 28 9 follows follow VERB bracis-28402 28 10 . . PUNCT bracis-28402 29 1 in in ADP bracis-28402 29 2 sect sect NOUN bracis-28402 29 3 . . PUNCT bracis-28402 29 4     SPACE bracis-28402 29 5 2 2 NUM bracis-28402 29 6 , , PUNCT bracis-28402 29 7 we we PRON bracis-28402 29 8 will will AUX bracis-28402 29 9 provide provide VERB bracis-28402 29 10 a a DET bracis-28402 29 11 brief brief ADJ bracis-28402 29 12 overview overview NOUN bracis-28402 29 13 of of ADP bracis-28402 29 14 statistical statistical ADJ bracis-28402 29 15 tests test NOUN bracis-28402 29 16 of of ADP bracis-28402 29 17 hypothesis hypothesis NOUN bracis-28402 29 18 and and CCONJ bracis-28402 29 19 their their PRON bracis-28402 29 20 application application NOUN bracis-28402 29 21 in in ADP bracis-28402 29 22 machine machine NOUN bracis-28402 29 23 learning learning NOUN bracis-28402 29 24 . . PUNCT bracis-28402 30 1 in in ADP bracis-28402 30 2 sects sect NOUN bracis-28402 30 3 . . PUNCT bracis-28402 30 4     SPACE bracis-28402 30 5 3 3 NUM bracis-28402 30 6 and and CCONJ bracis-28402 30 7 4 4 NUM bracis-28402 30 8 , , PUNCT bracis-28402 30 9 we we PRON bracis-28402 30 10 will will AUX bracis-28402 30 11 describe describe VERB bracis-28402 30 12 the the DET bracis-28402 30 13 experimental experimental ADJ bracis-28402 30 14 setup setup NOUN bracis-28402 30 15 and and CCONJ bracis-28402 30 16 datasets dataset NOUN bracis-28402 30 17 used use VERB bracis-28402 30 18 in in ADP bracis-28402 30 19 this this DET bracis-28402 30 20 study study NOUN bracis-28402 30 21 . . PUNCT bracis-28402 31 1 in in ADP bracis-28402 31 2 sect sect NOUN bracis-28402 31 3 . . PUNCT bracis-28402 31 4     SPACE bracis-28402 31 5 5 5 NUM bracis-28402 31 6 , , PUNCT bracis-28402 31 7 we we PRON bracis-28402 31 8 will will AUX bracis-28402 31 9 present present VERB bracis-28402 31 10 and and CCONJ bracis-28402 31 11 analyze analyze VERB bracis-28402 31 12 the the DET bracis-28402 31 13 results result NOUN bracis-28402 31 14 of of ADP bracis-28402 31 15 our our PRON bracis-28402 31 16 experiments experiment NOUN bracis-28402 31 17 . . PUNCT bracis-28402 32 1 finally finally ADV bracis-28402 32 2 , , PUNCT bracis-28402 32 3 in in ADP bracis-28402 32 4 sect sect NOUN bracis-28402 32 5 . . PUNCT bracis-28402 32 6     SPACE bracis-28402 32 7 6 6 NUM bracis-28402 32 8 , , PUNCT bracis-28402 32 9 we we PRON bracis-28402 32 10 will will AUX bracis-28402 32 11 conclude conclude VERB bracis-28402 32 12 the the DET bracis-28402 32 13 paper paper NOUN bracis-28402 32 14 with with ADP bracis-28402 32 15 a a DET bracis-28402 32 16 discussion discussion NOUN bracis-28402 32 17 of of ADP bracis-28402 32 18 the the DET bracis-28402 32 19 implications implication NOUN bracis-28402 32 20 of of ADP bracis-28402 32 21 our our PRON bracis-28402 32 22 findings finding NOUN bracis-28402 32 23 and and CCONJ bracis-28402 32 24 future future ADJ bracis-28402 32 25 research research NOUN bracis-28402 32 26 directions direction NOUN bracis-28402 32 27 . . PUNCT bracis-28402 33 1 2 2 NUM bracis-28402 33 2 statistical statistical ADJ bracis-28402 33 3 hypothesis hypothesis NOUN bracis-28402 33 4 testing testing NOUN bracis-28402 33 5 in in ADP bracis-28402 33 6 this this DET bracis-28402 33 7 section section NOUN bracis-28402 33 8 , , PUNCT bracis-28402 33 9 we we PRON bracis-28402 33 10 introduce introduce VERB bracis-28402 33 11 the the DET bracis-28402 33 12 hypothesis hypothesis NOUN bracis-28402 33 13 tests test NOUN bracis-28402 33 14 used use VERB bracis-28402 33 15 in in ADP bracis-28402 33 16 this this DET bracis-28402 33 17 study study NOUN bracis-28402 33 18 . . PUNCT bracis-28402 34 1 given give VERB bracis-28402 34 2 our our PRON bracis-28402 34 3 objective objective NOUN bracis-28402 34 4 of of ADP bracis-28402 34 5 comparing compare VERB bracis-28402 34 6 two two NUM bracis-28402 34 7 groups group NOUN bracis-28402 34 8 , , PUNCT bracis-28402 34 9 which which PRON bracis-28402 34 10 is be AUX bracis-28402 34 11 the the DET bracis-28402 34 12 simplest simple ADJ bracis-28402 34 13 scenario scenario NOUN bracis-28402 34 14 , , PUNCT bracis-28402 34 15 i.e. i.e. X bracis-28402 34 16 , , PUNCT bracis-28402 34 17 comparing compare VERB bracis-28402 34 18 two two NUM bracis-28402 34 19 algorithms algorithm NOUN bracis-28402 34 20 , , PUNCT bracis-28402 34 21 we we PRON bracis-28402 34 22 have have AUX bracis-28402 34 23 selected select VERB bracis-28402 34 24 methods method NOUN bracis-28402 34 25 for for ADP bracis-28402 34 26 this this DET bracis-28402 34 27 purpose purpose NOUN bracis-28402 34 28 . . PUNCT bracis-28402 35 1 we we PRON bracis-28402 35 2 have have AUX bracis-28402 35 3 chosen choose VERB bracis-28402 35 4 the the DET bracis-28402 35 5 t t NOUN bracis-28402 35 6 - - PUNCT bracis-28402 35 7 test test NOUN bracis-28402 35 8 as as ADP bracis-28402 35 9 a a DET bracis-28402 35 10 representative representative ADJ bracis-28402 35 11 parametric parametric ADJ bracis-28402 35 12 test test NOUN bracis-28402 35 13 , , PUNCT bracis-28402 35 14 while while SCONJ bracis-28402 35 15 the the DET bracis-28402 35 16 mann mann PROPN bracis-28402 35 17 - - PUNCT bracis-28402 35 18 whitney whitney PROPN bracis-28402 35 19 u u PROPN bracis-28402 35 20 test test NOUN bracis-28402 35 21 has have AUX bracis-28402 35 22 been be AUX bracis-28402 35 23 selected select VERB bracis-28402 35 24 as as ADP bracis-28402 35 25 the the DET bracis-28402 35 26 non non ADJ bracis-28402 35 27 - - ADJ bracis-28402 35 28 parametric parametric ADJ bracis-28402 35 29 option option NOUN bracis-28402 35 30 . . PUNCT bracis-28402 36 1 2.1 2.1 NUM bracis-28402 36 2 paired pair VERB bracis-28402 36 3 t t NOUN bracis-28402 36 4 - - PUNCT bracis-28402 36 5 test test NOUN bracis-28402 36 6 for for ADP bracis-28402 36 7     SPACE bracis-28402 36 8 two two NUM bracis-28402 36 9 related related ADJ bracis-28402 36 10 samples sample NOUN bracis-28402 36 11 a a DET bracis-28402 36 12 paired pair VERB bracis-28402 36 13 t t NOUN bracis-28402 36 14 - - PUNCT bracis-28402 36 15 test test NOUN bracis-28402 36 16 is be AUX bracis-28402 36 17 a a DET bracis-28402 36 18 statistical statistical ADJ bracis-28402 36 19 test test NOUN bracis-28402 36 20 used use VERB bracis-28402 36 21 to to PART bracis-28402 36 22 determine determine VERB bracis-28402 36 23 whether whether SCONJ bracis-28402 36 24 there there PRON bracis-28402 36 25 is be VERB bracis-28402 36 26 a a DET bracis-28402 36 27 significant significant ADJ bracis-28402 36 28 difference difference NOUN bracis-28402 36 29 between between ADP bracis-28402 36 30 the the DET bracis-28402 36 31 means mean NOUN bracis-28402 36 32 of of ADP bracis-28402 36 33 two two NUM bracis-28402 36 34 related related ADJ bracis-28402 36 35 samples sample NOUN bracis-28402 36 36 [ [ X bracis-28402 36 37 11 11 NUM bracis-28402 36 38 ] ] PUNCT bracis-28402 36 39 . . PUNCT bracis-28402 37 1 while while SCONJ bracis-28402 37 2 using use VERB bracis-28402 37 3 it it PRON bracis-28402 37 4 , , PUNCT bracis-28402 37 5 each each DET bracis-28402 37 6 individual individual NOUN bracis-28402 37 7 in in ADP bracis-28402 37 8 one one NUM bracis-28402 37 9 sample sample NOUN bracis-28402 37 10 is be AUX bracis-28402 37 11 paired pair VERB bracis-28402 37 12 with with ADP bracis-28402 37 13 an an DET bracis-28402 37 14 individual individual NOUN bracis-28402 37 15 in in ADP bracis-28402 37 16 the the DET bracis-28402 37 17 other other ADJ bracis-28402 37 18 sample sample NOUN bracis-28402 37 19 based base VERB bracis-28402 37 20 on on ADP bracis-28402 37 21 some some DET bracis-28402 37 22 common common ADJ bracis-28402 37 23 characteristic characteristic NOUN bracis-28402 37 24 , , PUNCT bracis-28402 37 25 such such ADJ bracis-28402 37 26 as as ADP bracis-28402 37 27 before before ADP bracis-28402 37 28 - - PUNCT bracis-28402 37 29 and and CCONJ bracis-28402 37 30 - - PUNCT bracis-28402 37 31 after after ADJ bracis-28402 37 32 measurements measurement NOUN bracis-28402 37 33 of of ADP bracis-28402 37 34 the the DET bracis-28402 37 35 same same ADJ bracis-28402 37 36 individual individual NOUN bracis-28402 37 37 , , PUNCT bracis-28402 37 38 or or CCONJ bracis-28402 37 39 measurements measurement NOUN bracis-28402 37 40 from from ADP bracis-28402 37 41 two two NUM bracis-28402 37 42 different different ADJ bracis-28402 37 43 methods method NOUN bracis-28402 37 44 applied apply VERB bracis-28402 37 45 to to ADP bracis-28402 37 46 the the DET bracis-28402 37 47 same same ADJ bracis-28402 37 48 subjects subject NOUN bracis-28402 37 49 . . PUNCT bracis-28402 38 1 it it PRON bracis-28402 38 2 assumes assume VERB bracis-28402 38 3 that that SCONJ bracis-28402 38 4 the the DET bracis-28402 38 5 two two NUM bracis-28402 38 6 samples sample NOUN bracis-28402 38 7 are be AUX bracis-28402 38 8 normally normally ADV bracis-28402 38 9 distributed distribute VERB bracis-28402 38 10 and and CCONJ bracis-28402 38 11 have have VERB bracis-28402 38 12 equal equal ADJ bracis-28402 38 13 variances variance NOUN bracis-28402 38 14 . . PUNCT bracis-28402 39 1 the the DET bracis-28402 39 2 null null ADJ bracis-28402 39 3 hypothesis hypothesis NOUN bracis-28402 39 4 of of ADP bracis-28402 39 5 the the DET bracis-28402 39 6 paired pair VERB bracis-28402 39 7 t t NOUN bracis-28402 39 8 - - PUNCT bracis-28402 39 9 test test NOUN bracis-28402 39 10 is be AUX bracis-28402 39 11 that that SCONJ bracis-28402 39 12 there there PRON bracis-28402 39 13 is be VERB bracis-28402 39 14 no no DET bracis-28402 39 15 difference difference NOUN bracis-28402 39 16 between between ADP bracis-28402 39 17 the the DET bracis-28402 39 18 means mean NOUN bracis-28402 39 19 of of ADP bracis-28402 39 20 the the DET bracis-28402 39 21 two two NUM bracis-28402 39 22 samples sample NOUN bracis-28402 39 23 . . PUNCT bracis-28402 40 1 if if SCONJ bracis-28402 40 2 the the DET bracis-28402 40 3 p p NOUN bracis-28402 40 4 - - PUNCT bracis-28402 40 5 value value NOUN bracis-28402 40 6 returned return VERB bracis-28402 40 7 by by ADP bracis-28402 40 8 it it PRON bracis-28402 40 9 , , PUNCT bracis-28402 40 10 which which PRON bracis-28402 40 11 is be AUX bracis-28402 40 12 a a DET bracis-28402 40 13 representation representation NOUN bracis-28402 40 14 of of ADP bracis-28402 40 15 the the DET bracis-28402 40 16 probability probability NOUN bracis-28402 40 17 of of ADP bracis-28402 40 18 obtaining obtain VERB bracis-28402 40 19 a a DET bracis-28402 40 20 statistic statistic NOUN bracis-28402 40 21 as as ADV bracis-28402 40 22 extreme extreme ADJ bracis-28402 40 23 as as SCONJ bracis-28402 40 24 the the DET bracis-28402 40 25 one one NUM bracis-28402 40 26 observed observe VERB bracis-28402 40 27 , , PUNCT bracis-28402 40 28 assuming assume VERB bracis-28402 40 29 that that SCONJ bracis-28402 40 30 the the DET bracis-28402 40 31 null null ADJ bracis-28402 40 32 hypothesis hypothesis NOUN bracis-28402 40 33 is be AUX bracis-28402 40 34 true true ADJ bracis-28402 40 35 , , PUNCT bracis-28402 40 36 is be AUX bracis-28402 40 37 less less ADJ bracis-28402 40 38 than than ADP bracis-28402 40 39 a a DET bracis-28402 40 40 predefined predefine VERB bracis-28402 40 41 significance significance NOUN bracis-28402 40 42 level level NOUN bracis-28402 40 43 ( ( PUNCT bracis-28402 40 44 e.g. e.g. ADV bracis-28402 40 45 , , PUNCT bracis-28402 40 46 0.05 0.05 NUM bracis-28402 40 47 ) ) PUNCT bracis-28402 40 48 , , PUNCT bracis-28402 40 49 the the DET bracis-28402 40 50 null null ADJ bracis-28402 40 51 hypothesis hypothesis NOUN bracis-28402 40 52 can can AUX bracis-28402 40 53 be be AUX bracis-28402 40 54 rejected reject VERB bracis-28402 40 55 , , PUNCT bracis-28402 40 56 and and CCONJ bracis-28402 40 57 it it PRON bracis-28402 40 58 usually usually ADV bracis-28402 40 59 concluded conclude VERB bracis-28402 40 60 that that SCONJ bracis-28402 40 61 there there PRON bracis-28402 40 62 is be VERB bracis-28402 40 63 a a DET bracis-28402 40 64 significant significant ADJ bracis-28402 40 65 difference difference NOUN bracis-28402 40 66 between between ADP bracis-28402 40 67 the the DET bracis-28402 40 68 means mean NOUN bracis-28402 40 69 of of ADP bracis-28402 40 70 the the DET bracis-28402 40 71 two two NUM bracis-28402 40 72 samples sample NOUN bracis-28402 40 73 . . PUNCT bracis-28402 41 1 the the DET bracis-28402 41 2 scipy.stats.ttest_rel scipy.stats.ttest_rel NOUN bracis-28402 41 3 function function NOUN bracis-28402 41 4 is be AUX bracis-28402 41 5 the the DET bracis-28402 41 6 method method NOUN bracis-28402 41 7 in in ADP bracis-28402 41 8 the the DET bracis-28402 41 9 scipy scipy NOUN bracis-28402 41 10 library library NOUN bracis-28402 42 1 [ [ X bracis-28402 42 2 16 16 NUM bracis-28402 42 3 ] ] PUNCT bracis-28402 42 4 that that PRON bracis-28402 42 5 performs perform VERB bracis-28402 42 6 a a DET bracis-28402 42 7 paired pair VERB bracis-28402 42 8 t t NOUN bracis-28402 42 9 - - PUNCT bracis-28402 42 10 test test NOUN bracis-28402 42 11 for for ADP bracis-28402 42 12 two two NUM bracis-28402 42 13 related relate VERB bracis-28402 42 14 samples sample NOUN bracis-28402 42 15 . . PUNCT bracis-28402 43 1 it it PRON bracis-28402 43 2 can can AUX bracis-28402 43 3 be be AUX bracis-28402 43 4 used use VERB bracis-28402 43 5 in in ADP bracis-28402 43 6 machine machine NOUN bracis-28402 43 7 learning learn VERB bracis-28402 43 8 to to PART bracis-28402 43 9 compare compare VERB bracis-28402 43 10 the the DET bracis-28402 43 11 performance performance NOUN bracis-28402 43 12 of of ADP bracis-28402 43 13 two two NUM bracis-28402 43 14 models model NOUN bracis-28402 43 15 on on ADP bracis-28402 43 16 the the DET bracis-28402 43 17 same same ADJ bracis-28402 43 18 dataset dataset NOUN bracis-28402 43 19 . . PUNCT bracis-28402 44 1 this this DET bracis-28402 44 2 information information NOUN bracis-28402 44 3 can can AUX bracis-28402 44 4 be be AUX bracis-28402 44 5 useful useful ADJ bracis-28402 44 6 in in ADP bracis-28402 44 7 model model NOUN bracis-28402 44 8 selection selection NOUN bracis-28402 44 9 and and CCONJ bracis-28402 44 10 can can AUX bracis-28402 44 11 help help VERB bracis-28402 44 12 to to PART bracis-28402 44 13 identify identify VERB bracis-28402 44 14 the the DET bracis-28402 44 15 best good ADJ bracis-28402 44 16 performing performing NOUN bracis-28402 44 17 model model NOUN bracis-28402 44 18 for for ADP bracis-28402 44 19 a a DET bracis-28402 44 20 given give VERB bracis-28402 44 21 task task NOUN bracis-28402 44 22 . . PUNCT bracis-28402 45 1 the the DET bracis-28402 45 2 test test NOUN bracis-28402 45 3 statistic statistic PROPN bracis-28402 45 4 t t PROPN bracis-28402 45 5 is be AUX bracis-28402 45 6 computed compute VERB bracis-28402 45 7 as as SCONJ bracis-28402 45 8 follows follow VERB bracis-28402 45 9 : : PUNCT bracis-28402 46 1 $ $ SYM bracis-28402 46 2 $ $ SYM bracis-28402 46 3 \begin{aligned \begin{aligne VERB bracis-28402 46 4 } } PUNCT bracis-28402 46 5 t t NOUN bracis-28402 46 6 = = SYM bracis-28402 46 7 \frac{\overline{x}_d \frac{\overline{x}_d PROPN bracis-28402 46 8 \mu \mu PROPN bracis-28402 46 9 _ _ PROPN bracis-28402 46 10 0}{s_d/\sqrt{n 0}{s_d/\sqrt{n PROPN bracis-28402 46 11 } } PUNCT bracis-28402 46 12 } } PUNCT bracis-28402 46 13 \end{aligned}$$ \end{aligned}$$ X bracis-28402 46 14 ( ( PUNCT bracis-28402 46 15 1 1 NUM bracis-28402 46 16 ) ) PUNCT bracis-28402 46 17 where where SCONJ bracis-28402 46 18 , , PUNCT bracis-28402 46 19 \(\overline{x}_d\ \(\overline{x}_d\ PROPN bracis-28402 46 20 ) ) PUNCT bracis-28402 46 21 and and CCONJ bracis-28402 46 22 \(s_d\ \(s_d\ NOUN bracis-28402 46 23 ) ) PUNCT bracis-28402 46 24 are be AUX bracis-28402 46 25 the the DET bracis-28402 46 26 average average ADJ bracis-28402 46 27 and and CCONJ bracis-28402 46 28 the the DET bracis-28402 46 29 standard standard ADJ bracis-28402 46 30 deviation deviation NOUN bracis-28402 46 31 of of ADP bracis-28402 46 32 the the DET bracis-28402 46 33 difference difference NOUN bracis-28402 46 34 between between ADP bracis-28402 46 35 all all DET bracis-28402 46 36 pairs pair NOUN bracis-28402 46 37 . . PUNCT bracis-28402 47 1 \(\mu \(\mu VERB bracis-28402 47 2 _ _ PUNCT bracis-28402 47 3 0\ 0\ X bracis-28402 47 4 ) ) PUNCT bracis-28402 47 5 is be AUX bracis-28402 47 6 the the DET bracis-28402 47 7 true true ADJ bracis-28402 47 8 mean mean NOUN bracis-28402 47 9 of of ADP bracis-28402 47 10 the the DET bracis-28402 47 11 difference difference NOUN bracis-28402 47 12 under under ADP bracis-28402 47 13 the the DET bracis-28402 47 14 null null ADJ bracis-28402 47 15 hypothesis hypothesis NOUN bracis-28402 47 16 . . PUNCT bracis-28402 48 1 it it PRON bracis-28402 48 2 is be AUX bracis-28402 48 3 zero zero NUM bracis-28402 48 4 if if SCONJ bracis-28402 48 5 we we PRON bracis-28402 48 6 want want VERB bracis-28402 48 7 to to PART bracis-28402 48 8 test test VERB bracis-28402 48 9 whether whether SCONJ bracis-28402 48 10 the the DET bracis-28402 48 11 average average NOUN bracis-28402 48 12 of of ADP bracis-28402 48 13 the the DET bracis-28402 48 14 difference difference NOUN bracis-28402 48 15 is be AUX bracis-28402 48 16 significant significant ADJ bracis-28402 48 17 . . PUNCT bracis-28402 49 1 the the DET bracis-28402 49 2 number number NOUN bracis-28402 49 3 of of ADP bracis-28402 49 4 pairs pair NOUN bracis-28402 49 5 is be AUX bracis-28402 49 6 represented represent VERB bracis-28402 49 7 by by ADP bracis-28402 49 8 n n CCONJ bracis-28402 49 9 , , PUNCT bracis-28402 49 10 which which PRON bracis-28402 49 11 is be AUX bracis-28402 49 12 also also ADV bracis-28402 49 13 used use VERB bracis-28402 49 14 to to PART bracis-28402 49 15 calculate calculate VERB bracis-28402 49 16 the the DET bracis-28402 49 17 degrees degree NOUN bracis-28402 49 18 of of ADP bracis-28402 49 19 freedom freedom NOUN bracis-28402 49 20 as as ADP bracis-28402 49 21 \(n-1\ \(n-1\ PROPN bracis-28402 49 22 ) ) PUNCT bracis-28402 49 23 . . PUNCT bracis-28402 50 1 2.2 2.2 NUM bracis-28402 50 2 independent independent ADJ bracis-28402 50 3 t t NOUN bracis-28402 50 4 - - PUNCT bracis-28402 50 5 test test NOUN bracis-28402 50 6 for for ADP bracis-28402 50 7     SPACE bracis-28402 50 8 two two NUM bracis-28402 50 9 independent independent ADJ bracis-28402 50 10 samples sample NOUN bracis-28402 50 11 an an DET bracis-28402 50 12 independent independent ADJ bracis-28402 50 13 t t NOUN bracis-28402 50 14 - - PUNCT bracis-28402 50 15 test test NOUN bracis-28402 50 16 is be AUX bracis-28402 50 17 a a DET bracis-28402 50 18 statistical statistical ADJ bracis-28402 50 19 test test NOUN bracis-28402 50 20 used use VERB bracis-28402 50 21 to to PART bracis-28402 50 22 determine determine VERB bracis-28402 50 23 whether whether SCONJ bracis-28402 50 24 there there PRON bracis-28402 50 25 is be VERB bracis-28402 50 26 a a DET bracis-28402 50 27 significant significant ADJ bracis-28402 50 28 difference difference NOUN bracis-28402 50 29 between between ADP bracis-28402 50 30 the the DET bracis-28402 50 31 means mean NOUN bracis-28402 50 32 of of ADP bracis-28402 50 33 two two NUM bracis-28402 50 34 independent independent ADJ bracis-28402 50 35 samples sample NOUN bracis-28402 50 36 . . PUNCT bracis-28402 51 1 the the DET bracis-28402 51 2 scipy.stats.ttest_ind scipy.stats.ttest_ind NOUN bracis-28402 51 3 function function NOUN bracis-28402 51 4 is be AUX bracis-28402 51 5 a a DET bracis-28402 51 6 method method NOUN bracis-28402 51 7 in in ADP bracis-28402 51 8 the the DET bracis-28402 51 9 scipy scipy NOUN bracis-28402 51 10 library library NOUN bracis-28402 52 1 [ [ X bracis-28402 52 2 16 16 NUM bracis-28402 52 3 ] ] PUNCT bracis-28402 52 4 that that PRON bracis-28402 52 5 performs perform VERB bracis-28402 52 6 an an DET bracis-28402 52 7 independent independent ADJ bracis-28402 52 8 t t NOUN bracis-28402 52 9 - - PUNCT bracis-28402 52 10 test test NOUN bracis-28402 52 11 for for ADP bracis-28402 52 12 two two NUM bracis-28402 52 13 independent independent ADJ bracis-28402 52 14 samples sample NOUN bracis-28402 52 15 . . PUNCT bracis-28402 53 1 it it PRON bracis-28402 53 2 assumes assume VERB bracis-28402 53 3 that that SCONJ bracis-28402 53 4 the the DET bracis-28402 53 5 two two NUM bracis-28402 53 6 samples sample NOUN bracis-28402 53 7 are be AUX bracis-28402 53 8 normally normally ADV bracis-28402 53 9 distributed distribute VERB bracis-28402 53 10 and and CCONJ bracis-28402 53 11 have have VERB bracis-28402 53 12 equal equal ADJ bracis-28402 53 13 variances variance NOUN bracis-28402 53 14 . . PUNCT bracis-28402 54 1 the the DET bracis-28402 54 2 null null ADJ bracis-28402 54 3 hypothesis hypothesis NOUN bracis-28402 54 4 of of ADP bracis-28402 54 5 the the DET bracis-28402 54 6 independent independent ADJ bracis-28402 54 7 t t PROPN bracis-28402 54 8 - - PUNCT bracis-28402 54 9 test test NOUN bracis-28402 54 10 is be AUX bracis-28402 54 11 that that SCONJ bracis-28402 54 12 there there PRON bracis-28402 54 13 is be VERB bracis-28402 54 14 no no DET bracis-28402 54 15 difference difference NOUN bracis-28402 54 16 between between ADP bracis-28402 54 17 the the DET bracis-28402 54 18 means mean NOUN bracis-28402 54 19 of of ADP bracis-28402 54 20 the the DET bracis-28402 54 21 two two NUM bracis-28402 54 22 samples sample NOUN bracis-28402 54 23 [ [ X bracis-28402 54 24 11 11 NUM bracis-28402 54 25 ] ] PUNCT bracis-28402 54 26 . . PUNCT bracis-28402 55 1 if if SCONJ bracis-28402 55 2 the the DET bracis-28402 55 3 p p NOUN bracis-28402 55 4 - - PUNCT bracis-28402 55 5 value value NOUN bracis-28402 55 6 returned return VERB bracis-28402 55 7 by by ADP bracis-28402 55 8 the the DET bracis-28402 55 9 ttest_ind ttest_ind NUM bracis-28402 55 10 function function NOUN bracis-28402 55 11 is be AUX bracis-28402 55 12 less less ADJ bracis-28402 55 13 than than ADP bracis-28402 55 14 a a DET bracis-28402 55 15 predefined predefine VERB bracis-28402 55 16 significance significance NOUN bracis-28402 55 17 level level NOUN bracis-28402 55 18 ( ( PUNCT bracis-28402 55 19 e.g. e.g. ADV bracis-28402 55 20 , , PUNCT bracis-28402 55 21 0.05 0.05 NUM bracis-28402 55 22 ) ) PUNCT bracis-28402 55 23 , , PUNCT bracis-28402 55 24 the the DET bracis-28402 55 25 null null ADJ bracis-28402 55 26 hypothesis hypothesis NOUN bracis-28402 55 27 can can AUX bracis-28402 55 28 be be AUX bracis-28402 55 29 rejected reject VERB bracis-28402 55 30 , , PUNCT bracis-28402 55 31 and and CCONJ bracis-28402 55 32 it it PRON bracis-28402 55 33 can can AUX bracis-28402 55 34 be be AUX bracis-28402 55 35 concluded conclude VERB bracis-28402 55 36 that that SCONJ bracis-28402 55 37 there there PRON bracis-28402 55 38 is be VERB bracis-28402 55 39 a a DET bracis-28402 55 40 significant significant ADJ bracis-28402 55 41 difference difference NOUN bracis-28402 55 42 between between ADP bracis-28402 55 43 the the DET bracis-28402 55 44 means mean NOUN bracis-28402 55 45 of of ADP bracis-28402 55 46 the the DET bracis-28402 55 47 two two NUM bracis-28402 55 48 samples sample NOUN bracis-28402 55 49 . . PUNCT bracis-28402 56 1 the the DET bracis-28402 56 2 test test NOUN bracis-28402 56 3 t t PROPN bracis-28402 56 4 statistic statistic NOUN bracis-28402 56 5 is be AUX bracis-28402 56 6 computed compute VERB bracis-28402 56 7 as as ADP bracis-28402 56 8 : : PUNCT bracis-28402 56 9 $ $ SYM bracis-28402 56 10 $ $ SYM bracis-28402 56 11 \begin{aligned \begin{aligne VERB bracis-28402 56 12 } } PUNCT bracis-28402 56 13 t t NOUN bracis-28402 56 14 = = SYM bracis-28402 56 15 \frac{\overline{x}_1 \frac{\overline{x}_1 PROPN bracis-28402 56 16 \overline{x}_2}{s_p \overline{x}_2}{s_p ADJ bracis-28402 56 17 \times \times ADP bracis-28402 56 18 \sqrt{\frac{1}{n_1 \sqrt{\frac{1}{n_1 NOUN bracis-28402 56 19 } } PUNCT bracis-28402 56 20 + + CCONJ bracis-28402 56 21 \frac{1}{n_2 \frac{1}{n_2 NOUN bracis-28402 56 22 } } PUNCT bracis-28402 56 23 } } PUNCT bracis-28402 56 24 } } PUNCT bracis-28402 56 25 \end{aligned}$$ \end{aligned}$$ X bracis-28402 56 26 ( ( PUNCT bracis-28402 56 27 2 2 NUM bracis-28402 56 28 ) ) PUNCT bracis-28402 56 29 where where SCONJ bracis-28402 56 30 $ $ SYM bracis-28402 56 31 $ $ SYM bracis-28402 56 32 \begin{aligned \begin{aligne VERB bracis-28402 56 33 } } PUNCT bracis-28402 56 34 s_p s_p NUM bracis-28402 57 1 = = PUNCT bracis-28402 57 2 \sqrt{\frac{(n_1 \sqrt{\frac{(n_1 PROPN bracis-28402 57 3 1)s^2_{x_1 1)s^2_{x_1 NUM bracis-28402 57 4 } } PUNCT bracis-28402 57 5 + + CCONJ bracis-28402 57 6 ( ( PUNCT bracis-28402 57 7 n_2 n_2 PROPN bracis-28402 57 8 1)s^2_{x_2}}{n_1 1)s^2_{x_2}}{n_1 PROPN bracis-28402 58 1 + + CCONJ bracis-28402 58 2 n_2 n_2 PROPN bracis-28402 58 3 2 2 NUM bracis-28402 58 4 } } PUNCT bracis-28402 58 5 } } PUNCT bracis-28402 58 6 \end{aligned}$$ \end{aligned}$$ X bracis-28402 58 7 ( ( PUNCT bracis-28402 58 8 3 3 NUM bracis-28402 58 9 ) ) PUNCT bracis-28402 58 10 \(s \( NOUN bracis-28402 58 11 _ _ PRON bracis-28402 59 1 p\ p\ NOUN bracis-28402 59 2 ) ) PUNCT bracis-28402 59 3 is be AUX bracis-28402 59 4 the the DET bracis-28402 59 5 pooled pooled ADJ bracis-28402 59 6 standard standard ADJ bracis-28402 59 7 deviation deviation NOUN bracis-28402 59 8 of of ADP bracis-28402 59 9 the the DET bracis-28402 59 10 two two NUM bracis-28402 59 11 samples sample NOUN bracis-28402 59 12 . . PUNCT bracis-28402 60 1 it it PRON bracis-28402 60 2 is be AUX bracis-28402 60 3 defined define VERB bracis-28402 60 4 in in ADP bracis-28402 60 5 this this DET bracis-28402 60 6 way way NOUN bracis-28402 60 7 so so SCONJ bracis-28402 60 8 that that SCONJ bracis-28402 60 9 its its PRON bracis-28402 60 10 square square NOUN bracis-28402 60 11 is be AUX bracis-28402 60 12 an an DET bracis-28402 60 13 unbiased unbiased ADJ bracis-28402 60 14 estimator estimator NOUN bracis-28402 60 15 of of ADP bracis-28402 60 16 the the DET bracis-28402 60 17 common common ADJ bracis-28402 60 18 variance variance NOUN bracis-28402 60 19 . . PUNCT bracis-28402 61 1 for for ADP bracis-28402 61 2 more more ADJ bracis-28402 61 3 details detail NOUN bracis-28402 61 4 , , PUNCT bracis-28402 61 5 see see VERB bracis-28402 61 6 [ [ X bracis-28402 61 7 12 12 NUM bracis-28402 61 8 ] ] PUNCT bracis-28402 61 9 . . PUNCT bracis-28402 62 1 2.3 2.3 NUM bracis-28402 62 2 mann mann PROPN bracis-28402 62 3 - - PUNCT bracis-28402 62 4 whitney whitney PROPN bracis-28402 62 5 u u PROPN bracis-28402 62 6 test test VERB bracis-28402 62 7 the the DET bracis-28402 62 8 mann mann PROPN bracis-28402 62 9 - - PUNCT bracis-28402 62 10 whitney whitney PROPN bracis-28402 62 11 u u PROPN bracis-28402 62 12 test test NOUN bracis-28402 62 13 is be AUX bracis-28402 62 14 a a DET bracis-28402 62 15 non non ADJ bracis-28402 62 16 - - ADJ bracis-28402 62 17 parametric parametric ADJ bracis-28402 62 18 statistical statistical ADJ bracis-28402 62 19 test test NOUN bracis-28402 62 20 used use VERB bracis-28402 62 21 to to PART bracis-28402 62 22 determine determine VERB bracis-28402 62 23 whether whether SCONJ bracis-28402 62 24 there there PRON bracis-28402 62 25 is be VERB bracis-28402 62 26 a a DET bracis-28402 62 27 significant significant ADJ bracis-28402 62 28 difference difference NOUN bracis-28402 62 29 between between ADP bracis-28402 62 30 the the DET bracis-28402 62 31 distributions distribution NOUN bracis-28402 62 32 of of ADP bracis-28402 62 33 two two NUM bracis-28402 62 34 independent independent ADJ bracis-28402 62 35 samples sample NOUN bracis-28402 62 36 . . PUNCT bracis-28402 63 1 the the DET bracis-28402 63 2 ss.mannwhitneyu ss.mannwhitneyu NOUN bracis-28402 63 3 function function NOUN bracis-28402 63 4 is be AUX bracis-28402 63 5 a a DET bracis-28402 63 6 method method NOUN bracis-28402 63 7 in in ADP bracis-28402 63 8 the the DET bracis-28402 63 9 scipy scipy NOUN bracis-28402 63 10 library library NOUN bracis-28402 63 11 [ [ X bracis-28402 63 12 16 16 NUM bracis-28402 63 13 ] ] PUNCT bracis-28402 63 14 that that PRON bracis-28402 63 15 performs perform VERB bracis-28402 63 16 the the DET bracis-28402 63 17 mann mann PROPN bracis-28402 63 18 - - PUNCT bracis-28402 63 19 whitney whitney PROPN bracis-28402 63 20 u u PROPN bracis-28402 63 21 test test NOUN bracis-28402 63 22 , , PUNCT bracis-28402 63 23 also also ADV bracis-28402 63 24 known know VERB bracis-28402 63 25 as as ADP bracis-28402 63 26 the the DET bracis-28402 63 27 wilcoxon wilcoxon ADJ bracis-28402 63 28 rank rank NOUN bracis-28402 63 29 - - PUNCT bracis-28402 63 30 sum sum NOUN bracis-28402 63 31 test test NOUN bracis-28402 63 32 . . PUNCT bracis-28402 64 1 a a DET bracis-28402 64 2 very very ADV bracis-28402 64 3 general general ADJ bracis-28402 64 4 formulation formulation NOUN bracis-28402 64 5 is be AUX bracis-28402 64 6 to to PART bracis-28402 64 7 assume assume VERB bracis-28402 64 8 that that SCONJ bracis-28402 64 9 : : PUNCT bracis-28402 64 10 all all DET bracis-28402 64 11 the the DET bracis-28402 64 12 observations observation NOUN bracis-28402 64 13 from from ADP bracis-28402 64 14 both both DET bracis-28402 64 15 groups group NOUN bracis-28402 64 16 are be AUX bracis-28402 64 17 independent independent ADJ bracis-28402 64 18 of of ADP bracis-28402 64 19 each each DET bracis-28402 64 20 other other ADJ bracis-28402 64 21 , , PUNCT bracis-28402 64 22 the the DET bracis-28402 64 23 responses response NOUN bracis-28402 64 24 are be AUX bracis-28402 64 25 at at ADP bracis-28402 64 26 least least ADJ bracis-28402 64 27 ordinal ordinal ADJ bracis-28402 64 28 ( ( PUNCT bracis-28402 64 29 i.e. i.e. X bracis-28402 64 30 , , PUNCT bracis-28402 64 31 one one PRON bracis-28402 64 32 can can AUX bracis-28402 64 33 at at ADV bracis-28402 64 34 least least ADJ bracis-28402 64 35 say say VERB bracis-28402 64 36 , , PUNCT bracis-28402 64 37 of of ADP bracis-28402 64 38 any any DET bracis-28402 64 39 two two NUM bracis-28402 64 40 observations observation NOUN bracis-28402 64 41 , , PUNCT bracis-28402 64 42 which which PRON bracis-28402 64 43 is be AUX bracis-28402 64 44 the the DET bracis-28402 64 45 greater great ADJ bracis-28402 64 46 ) ) PUNCT bracis-28402 64 47 , , PUNCT bracis-28402 64 48 under under ADP bracis-28402 64 49 the the DET bracis-28402 64 50 null null ADJ bracis-28402 64 51 hypothesis hypothesis NOUN bracis-28402 64 52 \(h_0\ \(h_0\ PROPN bracis-28402 64 53 ) ) PUNCT bracis-28402 64 54 , , PUNCT bracis-28402 64 55 the the DET bracis-28402 64 56 distributions distribution NOUN bracis-28402 64 57 of of ADP bracis-28402 64 58 both both DET bracis-28402 64 59 populations population NOUN bracis-28402 64 60 are be AUX bracis-28402 64 61 identical identical ADJ bracis-28402 64 62 . . PUNCT bracis-28402 65 1 the the DET bracis-28402 65 2 alternative alternative ADJ bracis-28402 65 3 hypothesis hypothesis NOUN bracis-28402 65 4 \(h_1\ \(h_1\ PROPN bracis-28402 65 5 ) ) PUNCT bracis-28402 65 6 is be AUX bracis-28402 65 7 that that SCONJ bracis-28402 65 8 the the DET bracis-28402 65 9 distributions distribution NOUN bracis-28402 65 10 are be AUX bracis-28402 65 11 not not PART bracis-28402 65 12 identical identical ADJ bracis-28402 65 13 . . PUNCT bracis-28402 66 1 the the DET bracis-28402 66 2 function function NOUN bracis-28402 66 3 takes take VERB bracis-28402 66 4 two two NUM bracis-28402 66 5 arrays array NOUN bracis-28402 66 6 of of ADP bracis-28402 66 7 different different ADJ bracis-28402 66 8 sizes size NOUN bracis-28402 66 9 as as ADP bracis-28402 66 10 input input NOUN bracis-28402 66 11 . . PUNCT bracis-28402 67 1 the the DET bracis-28402 67 2 arrays array NOUN bracis-28402 67 3 represent represent VERB bracis-28402 67 4 the the DET bracis-28402 67 5 two two NUM bracis-28402 67 6 samples sample NOUN bracis-28402 67 7 that that PRON bracis-28402 67 8 are be AUX bracis-28402 67 9 being be AUX bracis-28402 67 10 compared compare VERB bracis-28402 67 11 . . PUNCT bracis-28402 68 1 the the DET bracis-28402 68 2 function function NOUN bracis-28402 68 3 returns return VERB bracis-28402 68 4 two two NUM bracis-28402 68 5 values value NOUN bracis-28402 68 6 : : PUNCT bracis-28402 68 7 the the DET bracis-28402 68 8 calculated calculated ADJ bracis-28402 68 9 u u NOUN bracis-28402 68 10 statistic statistic NOUN bracis-28402 68 11 and and CCONJ bracis-28402 68 12 the the DET bracis-28402 68 13 associated associated ADJ bracis-28402 68 14 p p NOUN bracis-28402 68 15 - - PUNCT bracis-28402 68 16 value value NOUN bracis-28402 68 17 . . PUNCT bracis-28402 69 1 the the DET bracis-28402 69 2 u u PROPN bracis-28402 69 3 statistic statistic NOUN bracis-28402 69 4 is be AUX bracis-28402 69 5 a a DET bracis-28402 69 6 measure measure NOUN bracis-28402 69 7 of of ADP bracis-28402 69 8 the the DET bracis-28402 69 9 difference difference NOUN bracis-28402 69 10 between between ADP bracis-28402 69 11 the the DET bracis-28402 69 12 ranks rank NOUN bracis-28402 69 13 of of ADP bracis-28402 69 14 the the DET bracis-28402 69 15 two two NUM bracis-28402 69 16 samples sample NOUN bracis-28402 69 17 . . PUNCT bracis-28402 70 1 the the DET bracis-28402 70 2 null null ADJ bracis-28402 70 3 hypothesis hypothesis NOUN bracis-28402 70 4 of of ADP bracis-28402 70 5 the the DET bracis-28402 70 6 mann mann PROPN bracis-28402 70 7 - - PUNCT bracis-28402 70 8 whitney whitney PROPN bracis-28402 70 9 u u PROPN bracis-28402 70 10 test test NOUN bracis-28402 70 11 is be AUX bracis-28402 70 12 that that SCONJ bracis-28402 70 13 there there PRON bracis-28402 70 14 is be VERB bracis-28402 70 15 no no DET bracis-28402 70 16 difference difference NOUN bracis-28402 70 17 between between ADP bracis-28402 70 18 the the DET bracis-28402 70 19 distributions distribution NOUN bracis-28402 70 20 of of ADP bracis-28402 70 21 the the DET bracis-28402 70 22 two two NUM bracis-28402 70 23 samples sample NOUN bracis-28402 70 24 . . PUNCT bracis-28402 71 1 if if SCONJ bracis-28402 71 2 the the DET bracis-28402 71 3 p p NOUN bracis-28402 71 4 - - PUNCT bracis-28402 71 5 value value NOUN bracis-28402 71 6 returned return VERB bracis-28402 71 7 by by ADP bracis-28402 71 8 the the DET bracis-28402 71 9 ss.mannwhitneyu ss.mannwhitneyu NOUN bracis-28402 71 10 function function NOUN bracis-28402 71 11 is be AUX bracis-28402 71 12 less less ADJ bracis-28402 71 13 than than ADP bracis-28402 71 14 a a DET bracis-28402 71 15 predefined predefine VERB bracis-28402 71 16 significance significance NOUN bracis-28402 71 17 level level NOUN bracis-28402 71 18 ( ( PUNCT bracis-28402 71 19 e.g. e.g. ADV bracis-28402 71 20 , , PUNCT bracis-28402 71 21 0.05 0.05 NUM bracis-28402 71 22 ) ) PUNCT bracis-28402 71 23 , , PUNCT bracis-28402 71 24 the the DET bracis-28402 71 25 null null ADJ bracis-28402 71 26 hypothesis hypothesis NOUN bracis-28402 71 27 can can AUX bracis-28402 71 28 be be AUX bracis-28402 71 29 rejected reject VERB bracis-28402 71 30 , , PUNCT bracis-28402 71 31 and and CCONJ bracis-28402 71 32 it it PRON bracis-28402 71 33 can can AUX bracis-28402 71 34 be be AUX bracis-28402 71 35 concluded conclude VERB bracis-28402 71 36 that that SCONJ bracis-28402 71 37 there there PRON bracis-28402 71 38 is be VERB bracis-28402 71 39 a a DET bracis-28402 71 40 significant significant ADJ bracis-28402 71 41 difference difference NOUN bracis-28402 71 42 between between ADP bracis-28402 71 43 the the DET bracis-28402 71 44 distributions distribution NOUN bracis-28402 71 45 of of ADP bracis-28402 71 46 the the DET bracis-28402 71 47 two two NUM bracis-28402 71 48 samples sample NOUN bracis-28402 71 49 . . PUNCT bracis-28402 72 1 the the DET bracis-28402 72 2 mann mann PROPN bracis-28402 72 3 - - PUNCT bracis-28402 72 4 whitney whitney PROPN bracis-28402 72 5 u u PROPN bracis-28402 72 6 test test NOUN bracis-28402 72 7 is be AUX bracis-28402 72 8 commonly commonly ADV bracis-28402 72 9 used use VERB bracis-28402 72 10 in in ADP bracis-28402 72 11 machine machine NOUN bracis-28402 72 12 learning learn VERB bracis-28402 72 13 to to PART bracis-28402 72 14 compare compare VERB bracis-28402 72 15 the the DET bracis-28402 72 16 performance performance NOUN bracis-28402 72 17 of of ADP bracis-28402 72 18 two two NUM bracis-28402 72 19 models model NOUN bracis-28402 72 20 , , PUNCT bracis-28402 72 21 especially especially ADV bracis-28402 72 22 when when SCONJ bracis-28402 72 23 the the DET bracis-28402 72 24 assumptions assumption NOUN bracis-28402 72 25 of of ADP bracis-28402 72 26 the the DET bracis-28402 72 27 t t NOUN bracis-28402 72 28 - - PUNCT bracis-28402 72 29 test test NOUN bracis-28402 72 30 ( ( PUNCT bracis-28402 72 31 such such ADJ bracis-28402 72 32 as as ADP bracis-28402 72 33 normality normality NOUN bracis-28402 72 34 and and CCONJ bracis-28402 72 35 equal equal ADJ bracis-28402 72 36 variances variance NOUN bracis-28402 72 37 ) ) PUNCT bracis-28402 72 38 are be AUX bracis-28402 72 39 not not PART bracis-28402 72 40 met meet VERB bracis-28402 72 41 . . PUNCT bracis-28402 73 1 in in ADP bracis-28402 73 2 details detail NOUN bracis-28402 73 3 , , PUNCT bracis-28402 73 4 let let VERB bracis-28402 73 5 \(x_1 \(x_1 PROPN bracis-28402 73 6 , , PUNCT bracis-28402 73 7 \cdots \cdots PROPN bracis-28402 73 8 , , PUNCT bracis-28402 73 9 x_n\ x_n\ PROPN bracis-28402 73 10 ) ) PUNCT bracis-28402 73 11 be be VERB bracis-28402 73 12 an an DET bracis-28402 73 13 independent independent ADJ bracis-28402 73 14 and and CCONJ bracis-28402 73 15 identically identically ADV bracis-28402 73 16 distributed distribute VERB bracis-28402 73 17 ( ( PUNCT bracis-28402 73 18 i.i.d i.i.d ADJ bracis-28402 73 19 . . PUNCT bracis-28402 73 20 ) ) PUNCT bracis-28402 74 1 sample sample NOUN bracis-28402 74 2 from from ADP bracis-28402 74 3 x x PUNCT bracis-28402 74 4 and and CCONJ bracis-28402 74 5 \(y_1 \(y_1 PROPN bracis-28402 74 6 , , PUNCT bracis-28402 74 7 \cdots \cdot NOUN bracis-28402 74 8 , , PUNCT bracis-28402 74 9 y_m\ y_m\ PROPN bracis-28402 74 10 ) ) PUNCT bracis-28402 74 11 an an DET bracis-28402 74 12 i.i.d i.i.d NOUN bracis-28402 74 13 . . PUNCT bracis-28402 75 1 sample sample NOUN bracis-28402 75 2 from from ADP bracis-28402 75 3 y y PROPN bracis-28402 75 4 and and CCONJ bracis-28402 75 5 each each DET bracis-28402 75 6 sample sample NOUN bracis-28402 75 7 independent independent ADJ bracis-28402 75 8 from from ADP bracis-28402 75 9 another another PRON bracis-28402 75 10 . . PUNCT bracis-28402 76 1 the the DET bracis-28402 76 2 corresponding corresponding ADJ bracis-28402 76 3 mann mann PROPN bracis-28402 76 4 - - PUNCT bracis-28402 76 5 whitney whitney PROPN bracis-28402 76 6 u u PROPN bracis-28402 76 7 statistic statistic NOUN bracis-28402 76 8 is be AUX bracis-28402 76 9 defined define VERB bracis-28402 76 10 as as ADP bracis-28402 76 11 : : PUNCT bracis-28402 76 12 $ $ SYM bracis-28402 76 13 $ $ SYM bracis-28402 76 14 \begin{aligned \begin{aligne VERB bracis-28402 76 15 } } PUNCT bracis-28402 76 16 u u NOUN bracis-28402 76 17 = = NOUN bracis-28402 76 18 \sum \sum NOUN bracis-28402 76 19 _ _ PUNCT bracis-28402 76 20 { { PUNCT bracis-28402 76 21 i=1}^n\sum i=1}^n\sum X bracis-28402 76 22 _ _ PRON bracis-28402 76 23 { { PUNCT bracis-28402 76 24 j=1}^m j=1}^m PROPN bracis-28402 76 25 s\left s\left PROPN bracis-28402 76 26 ( ( PUNCT bracis-28402 76 27 x_i x_i X bracis-28402 76 28 , , PUNCT bracis-28402 76 29 y_j y_j SYM bracis-28402 77 1 \right \right NOUN bracis-28402 77 2 ) ) PUNCT bracis-28402 77 3 \end{aligned}$$ \end{aligned}$$ X bracis-28402 77 4 ( ( PUNCT bracis-28402 77 5 4 4 NUM bracis-28402 77 6 ) ) PUNCT bracis-28402 77 7 with with ADP bracis-28402 77 8 $ $ SYM bracis-28402 77 9 $ $ SYM bracis-28402 77 10 \begin{aligned \begin{aligne VERB bracis-28402 77 11 } } PUNCT bracis-28402 77 12 s(x s(x PROPN bracis-28402 77 13 , , PUNCT bracis-28402 77 14 y y NOUN bracis-28402 77 15 ) ) PUNCT bracis-28402 77 16 = = SYM bracis-28402 77 17 { { PUNCT bracis-28402 77 18 \left\ \left\ PROPN bracis-28402 77 19 { { PUNCT bracis-28402 77 20 \begin{array}{ll \begin{array}{ll PROPN bracis-28402 77 21 } } PUNCT bracis-28402 77 22 1 1 NUM bracis-28402 77 23 , , PUNCT bracis-28402 78 1 \text \text INTJ bracis-28402 78 2 { { PUNCT bracis-28402 78 3 if if SCONJ bracis-28402 78 4 } } PUNCT bracis-28402 78 5 x x PUNCT bracis-28402 78 6 > > X bracis-28402 78 7 y y PROPN bracis-28402 78 8 \\ \\ NOUN bracis-28402 78 9 0.5 0.5 NUM bracis-28402 78 10 , , PUNCT bracis-28402 78 11 \text \text ADP bracis-28402 78 12 { { PUNCT bracis-28402 78 13 if if SCONJ bracis-28402 78 14 } } PUNCT bracis-28402 78 15 x x X bracis-28402 78 16 = = PUNCT bracis-28402 78 17 y\\ y\\ NOUN bracis-28402 78 18 0 0 NUM bracis-28402 78 19 , , PUNCT bracis-28402 78 20 \text \text ADP bracis-28402 78 21 { { PUNCT bracis-28402 78 22 if if SCONJ bracis-28402 78 23 } } PUNCT bracis-28402 78 24 x x X bracis-28402 78 25 < < X bracis-28402 78 26 y y PROPN bracis-28402 78 27 \\ \\ NOUN bracis-28402 78 28 \end{array}\right \end{array}\right PROPN bracis-28402 78 29 . . PUNCT bracis-28402 78 30 } } PUNCT bracis-28402 78 31 \end{aligned}$$ \end{aligned}$$ X bracis-28402 78 32 ( ( PUNCT bracis-28402 78 33 5 5 NUM bracis-28402 78 34 ) ) PUNCT bracis-28402 78 35 for for ADP bracis-28402 78 36 large large ADJ bracis-28402 78 37 samples sample NOUN bracis-28402 78 38 , , PUNCT bracis-28402 78 39 assign assign VERB bracis-28402 78 40 numeric numeric ADJ bracis-28402 78 41 rank rank NOUN bracis-28402 78 42 to to ADP bracis-28402 78 43 all all DET bracis-28402 78 44 the the DET bracis-28402 78 45 observations observation NOUN bracis-28402 78 46 , , PUNCT bracis-28402 78 47 independent independent ADJ bracis-28402 78 48 of of ADP bracis-28402 78 49 the the DET bracis-28402 78 50 group group NOUN bracis-28402 78 51 they they PRON bracis-28402 78 52 are be AUX bracis-28402 78 53 . . PUNCT bracis-28402 79 1 then then ADV bracis-28402 79 2 , , PUNCT bracis-28402 79 3 u u NOUN bracis-28402 79 4 is be AUX bracis-28402 79 5 given give VERB bracis-28402 79 6 by by ADP bracis-28402 79 7 \(min(u_1 \(min(u_1 PROPN bracis-28402 79 8 , , PUNCT bracis-28402 79 9 u_2)\ u_2)\ PROPN bracis-28402 79 10 ) ) PUNCT bracis-28402 79 11 , , PUNCT bracis-28402 79 12 where where SCONJ bracis-28402 79 13 : : PUNCT bracis-28402 79 14 \(u_1 \(u_1 PROPN bracis-28402 79 15 = = SYM bracis-28402 79 16 n_1 n_1 PROPN bracis-28402 79 17 n_2 n_2 PROPN bracis-28402 79 18 + + CCONJ bracis-28402 79 19 \frac{n_1(n_1 \frac{n_1(n_1 PROPN bracis-28402 79 20 + + CCONJ bracis-28402 79 21 1)}{2 1)}{2 NUM bracis-28402 79 22 } } PUNCT bracis-28402 79 23 r_1,\ r_1,\ PROPN bracis-28402 79 24 ) ) PUNCT bracis-28402 79 25 and and CCONJ bracis-28402 79 26 \(u_2 \(u_2 PROPN bracis-28402 79 27 = = PROPN bracis-28402 79 28 n_1 n_1 PROPN bracis-28402 79 29 n_2 n_2 PROPN bracis-28402 80 1 + + CCONJ bracis-28402 80 2 \frac{n_2(n_2 \frac{n_2(n_2 NOUN bracis-28402 80 3 + + CCONJ bracis-28402 80 4 1)}{2 1)}{2 NUM bracis-28402 80 5 } } PUNCT bracis-28402 80 6 r_2\ r_2\ PROPN bracis-28402 80 7 ) ) PUNCT bracis-28402 80 8 . . PUNCT bracis-28402 81 1 \(r_i\ \(r_i\ NOUN bracis-28402 81 2 ) ) PUNCT bracis-28402 81 3 is be AUX bracis-28402 81 4 the the DET bracis-28402 81 5 sum sum NOUN bracis-28402 81 6 of of ADP bracis-28402 81 7 the the DET bracis-28402 81 8 ranks rank NOUN bracis-28402 81 9 from from ADP bracis-28402 81 10 observations observation NOUN bracis-28402 81 11 of of ADP bracis-28402 81 12 the the DET bracis-28402 81 13 group group NOUN bracis-28402 81 14 i i PRON bracis-28402 81 15 and and CCONJ bracis-28402 81 16 \(n_i\ \(n_i\ NOUN bracis-28402 81 17 ) ) PUNCT bracis-28402 82 1 is be AUX bracis-28402 82 2 the the DET bracis-28402 82 3 sample sample NOUN bracis-28402 82 4 size size NOUN bracis-28402 82 5 of of ADP bracis-28402 82 6 the the DET bracis-28402 82 7 group group NOUN bracis-28402 82 8 i. i. PROPN bracis-28402 82 9 3 3 NUM bracis-28402 82 10 the the DET bracis-28402 82 11 test test NOUN bracis-28402 82 12 bed bed NOUN bracis-28402 82 13 to to PART bracis-28402 82 14 evaluate evaluate VERB bracis-28402 82 15 the the DET bracis-28402 82 16 impact impact NOUN bracis-28402 82 17 of of ADP bracis-28402 82 18 using use VERB bracis-28402 82 19 the the DET bracis-28402 82 20 aforementioned aforementioned ADJ bracis-28402 82 21 statistical statistical ADJ bracis-28402 82 22 tests test NOUN bracis-28402 82 23 for for ADP bracis-28402 82 24 model model NOUN bracis-28402 82 25 selection selection NOUN bracis-28402 82 26 over over ADP bracis-28402 82 27 time time NOUN bracis-28402 82 28 , , PUNCT bracis-28402 82 29 a a DET bracis-28402 82 30 simplified simplified ADJ bracis-28402 82 31 evolutionary evolutionary ADJ bracis-28402 82 32 algorithm algorithm NOUN bracis-28402 82 33 is be AUX bracis-28402 82 34 defined define VERB bracis-28402 82 35 . . PUNCT bracis-28402 83 1 this this DET bracis-28402 83 2 algorithm algorithm NOUN bracis-28402 83 3 operates operate VERB bracis-28402 83 4 on on ADP bracis-28402 83 5 a a DET bracis-28402 83 6 population population NOUN bracis-28402 83 7 of of ADP bracis-28402 83 8 n n PRON bracis-28402 83 9 model model NOUN bracis-28402 83 10 types type NOUN bracis-28402 83 11 , , PUNCT bracis-28402 83 12 each each PRON bracis-28402 83 13 having have VERB bracis-28402 83 14 a a DET bracis-28402 83 15 set set NOUN bracis-28402 83 16 of of ADP bracis-28402 83 17 associated associated ADJ bracis-28402 83 18 hyper hyper NOUN bracis-28402 83 19 - - NOUN bracis-28402 83 20 parameters parameter NOUN bracis-28402 83 21 . . PUNCT bracis-28402 84 1 the the DET bracis-28402 84 2 model model NOUN bracis-28402 84 3 with with ADP bracis-28402 84 4 the the DET bracis-28402 84 5 highest high ADJ bracis-28402 84 6 performance performance NOUN bracis-28402 84 7 , , PUNCT bracis-28402 84 8 according accord VERB bracis-28402 84 9 to to ADP bracis-28402 84 10 metric metric PROPN bracis-28402 84 11 m m PROPN bracis-28402 84 12 , , PUNCT bracis-28402 84 13 is be AUX bracis-28402 84 14 designated designate VERB bracis-28402 84 15 as as ADP bracis-28402 84 16 best good ADJ bracis-28402 84 17 model model NOUN bracis-28402 84 18 . . PUNCT bracis-28402 85 1 during during ADP bracis-28402 85 2 each each DET bracis-28402 85 3 generation generation NOUN bracis-28402 85 4 , , PUNCT bracis-28402 85 5 a a DET bracis-28402 85 6 random random ADJ bracis-28402 85 7 model model NOUN bracis-28402 85 8 type type NOUN bracis-28402 85 9 is be AUX bracis-28402 85 10 selected select VERB bracis-28402 85 11 and and CCONJ bracis-28402 85 12 its its PRON bracis-28402 85 13 parameters parameter NOUN bracis-28402 85 14 undergo undergo VERB bracis-28402 85 15 random random ADJ bracis-28402 85 16 mutations mutation NOUN bracis-28402 85 17 . . PUNCT bracis-28402 86 1 the the DET bracis-28402 86 2 mutated mutate VERB bracis-28402 86 3 model model NOUN bracis-28402 86 4 then then ADV bracis-28402 86 5 competes compete VERB bracis-28402 86 6 with with ADP bracis-28402 86 7 the the DET bracis-28402 86 8 model model NOUN bracis-28402 86 9 of of ADP bracis-28402 86 10 the the DET bracis-28402 86 11 same same ADJ bracis-28402 86 12 type type NOUN bracis-28402 86 13 in in ADP bracis-28402 86 14 the the DET bracis-28402 86 15 population population NOUN bracis-28402 86 16 . . PUNCT bracis-28402 87 1 if if SCONJ bracis-28402 87 2 a a DET bracis-28402 87 3 statistical statistical ADJ bracis-28402 87 4 test test NOUN bracis-28402 87 5 reveals reveal VERB bracis-28402 87 6 a a DET bracis-28402 87 7 significant significant ADJ bracis-28402 87 8 difference difference NOUN bracis-28402 87 9 in in ADP bracis-28402 87 10 performance performance NOUN bracis-28402 87 11 at at ADP bracis-28402 87 12 a a DET bracis-28402 87 13 significance significance NOUN bracis-28402 87 14 level level NOUN bracis-28402 87 15 of of ADP bracis-28402 87 16 \(\alpha \(\alpha NOUN bracis-28402 87 17 = = SYM bracis-28402 87 18 0.05\ 0.05\ NUM bracis-28402 87 19 ) ) PUNCT bracis-28402 87 20 , , PUNCT bracis-28402 87 21 the the DET bracis-28402 87 22 hyper hyper NOUN bracis-28402 87 23 - - NOUN bracis-28402 87 24 parameters parameter NOUN bracis-28402 87 25 of of ADP bracis-28402 87 26 the the DET bracis-28402 87 27 model model NOUN bracis-28402 87 28 in in ADP bracis-28402 87 29 the the DET bracis-28402 87 30 population population NOUN bracis-28402 87 31 are be AUX bracis-28402 87 32 updated update VERB bracis-28402 87 33 . . PUNCT bracis-28402 88 1 in in ADP bracis-28402 88 2 such such ADJ bracis-28402 88 3 cases case NOUN bracis-28402 88 4 , , PUNCT bracis-28402 88 5 the the DET bracis-28402 88 6 mutated mutate VERB bracis-28402 88 7 model model NOUN bracis-28402 88 8 also also ADV bracis-28402 88 9 competes compete VERB bracis-28402 88 10 against against ADP bracis-28402 88 11 the the DET bracis-28402 88 12 current current ADJ bracis-28402 88 13 best good ADJ bracis-28402 88 14 model model NOUN bracis-28402 88 15 using use VERB bracis-28402 88 16 the the DET bracis-28402 88 17 same same ADJ bracis-28402 88 18 process process NOUN bracis-28402 88 19 . . PUNCT bracis-28402 89 1 ultimately ultimately ADV bracis-28402 89 2 , , PUNCT bracis-28402 89 3 the the DET bracis-28402 89 4 method method NOUN bracis-28402 89 5 returns return VERB bracis-28402 89 6 the the DET bracis-28402 89 7 best good ADJ bracis-28402 89 8 model model NOUN bracis-28402 89 9 obtained obtain VERB bracis-28402 89 10 through through ADP bracis-28402 89 11 this this DET bracis-28402 89 12 evolutionary evolutionary ADJ bracis-28402 89 13 process process NOUN bracis-28402 89 14 . . PUNCT bracis-28402 90 1 a a DET bracis-28402 90 2 pseudocode pseudocode NOUN bracis-28402 90 3 for for ADP bracis-28402 90 4 the the DET bracis-28402 90 5 method method NOUN bracis-28402 90 6 is be AUX bracis-28402 90 7 given give VERB bracis-28402 90 8 in in ADP bracis-28402 90 9 algorithm algorithm NOUN bracis-28402 90 10     SPACE bracis-28402 90 11 1 1 NUM bracis-28402 90 12 . . PUNCT bracis-28402 90 13 algorithm algorithm PROPN bracis-28402 90 14 19 19 NUM bracis-28402 90 15 . . PUNCT bracis-28402 91 1 evolutionary evolutionary ADJ bracis-28402 91 2 model model NOUN bracis-28402 91 3 selection selection NOUN bracis-28402 91 4 full full ADJ bracis-28402 91 5 size size NOUN bracis-28402 91 6 image image NOUN bracis-28402 91 7 4 4 NUM bracis-28402 91 8 experimental experimental ADJ bracis-28402 91 9 setup setup NOUN bracis-28402 91 10 4.1 4.1 NUM bracis-28402 91 11 datasets dataset NOUN bracis-28402 91 12 four four NUM bracis-28402 91 13 binary binary ADJ bracis-28402 91 14 classification classification NOUN bracis-28402 91 15 problems problem NOUN bracis-28402 91 16 defined define VERB bracis-28402 91 17 over over ADP bracis-28402 91 18 four four NUM bracis-28402 91 19 datasets dataset NOUN bracis-28402 91 20 from from ADP bracis-28402 91 21 the the DET bracis-28402 91 22 uci uci PROPN bracis-28402 91 23 repository repository NOUN bracis-28402 91 24 [ [ X bracis-28402 91 25 6 6 NUM bracis-28402 91 26 ] ] PUNCT bracis-28402 91 27 were be AUX bracis-28402 91 28 selected select VERB bracis-28402 91 29 for for ADP bracis-28402 91 30 analysis analysis NOUN bracis-28402 91 31 . . PUNCT bracis-28402 92 1 they they PRON bracis-28402 92 2 are be AUX bracis-28402 92 3 described describe VERB bracis-28402 92 4 below below ADP bracis-28402 92 5 : : PUNCT bracis-28402 93 1 1 1 X bracis-28402 93 2 . . X bracis-28402 93 3 the the DET bracis-28402 93 4 banking banking NOUN bracis-28402 93 5 dataset dataset NOUN bracis-28402 93 6 marketing marketing NOUN bracis-28402 93 7 targets target NOUN bracis-28402 93 8 [ [ X bracis-28402 93 9 13 13 NUM bracis-28402 93 10 ] ] PUNCT bracis-28402 93 11 ( ( PUNCT bracis-28402 93 12 banking banking NOUN bracis-28402 93 13 ) ) PUNCT bracis-28402 93 14 represents represent VERB bracis-28402 93 15 customer customer NOUN bracis-28402 93 16 data datum NOUN bracis-28402 93 17 in in ADP bracis-28402 93 18 the the DET bracis-28402 93 19 banking banking NOUN bracis-28402 93 20 industry industry NOUN bracis-28402 93 21 for for ADP bracis-28402 93 22 predicting predict VERB bracis-28402 93 23 conversion conversion NOUN bracis-28402 93 24 . . PUNCT bracis-28402 94 1 it it PRON bracis-28402 94 2 features feature VERB bracis-28402 94 3 a a DET bracis-28402 94 4 large large ADJ bracis-28402 94 5 sample sample NOUN bracis-28402 94 6 size size NOUN bracis-28402 94 7 ( ( PUNCT bracis-28402 94 8 \(n \(n NOUN bracis-28402 94 9 \approx \approx PROPN bracis-28402 94 10 45000\ 45000\ NUM bracis-28402 94 11 ) ) PUNCT bracis-28402 94 12 ) ) PUNCT bracis-28402 94 13 and and CCONJ bracis-28402 94 14 includes include VERB bracis-28402 94 15 seventeen seventeen NUM bracis-28402 94 16 predictors predictor NOUN bracis-28402 94 17 , , PUNCT bracis-28402 94 18 consisting consist VERB bracis-28402 94 19 of of ADP bracis-28402 94 20 seven seven NUM bracis-28402 94 21 numeric numeric ADJ bracis-28402 94 22 and and CCONJ bracis-28402 94 23 nine nine NUM bracis-28402 94 24 categorical categorical ADJ bracis-28402 94 25 variables variable NOUN bracis-28402 94 26 ( ( PUNCT bracis-28402 94 27 three three NUM bracis-28402 94 28 of of ADP bracis-28402 94 29 which which PRON bracis-28402 94 30 are be AUX bracis-28402 94 31 binary binary ADJ bracis-28402 94 32 ) ) PUNCT bracis-28402 94 33 . . PUNCT bracis-28402 95 1 2 2 X bracis-28402 95 2 . . X bracis-28402 95 3 the the DET bracis-28402 95 4 default default NOUN bracis-28402 95 5 of of ADP bracis-28402 95 6 credit credit NOUN bracis-28402 95 7 card card NOUN bracis-28402 95 8 clients client NOUN bracis-28402 95 9 dataset dataset VERB bracis-28402 95 10 [ [ X bracis-28402 95 11 18 18 NUM bracis-28402 95 12 ] ] PUNCT bracis-28402 95 13 ( ( PUNCT bracis-28402 95 14 credit credit NOUN bracis-28402 95 15 ) ) PUNCT bracis-28402 95 16 contains contain VERB bracis-28402 95 17 information information NOUN bracis-28402 95 18 about about ADP bracis-28402 95 19 default default NOUN bracis-28402 95 20 payments payment NOUN bracis-28402 95 21 of of ADP bracis-28402 95 22 credit credit NOUN bracis-28402 95 23 card card NOUN bracis-28402 95 24 clients client NOUN bracis-28402 95 25 in in ADP bracis-28402 95 26 taiwan taiwan PROPN bracis-28402 95 27 from from ADP bracis-28402 95 28 2005 2005 NUM bracis-28402 95 29 . . PUNCT bracis-28402 96 1 with with ADP bracis-28402 96 2 a a DET bracis-28402 96 3 substantial substantial ADJ bracis-28402 96 4 sample sample NOUN bracis-28402 96 5 size size NOUN bracis-28402 96 6 ( ( PUNCT bracis-28402 96 7 \(n \(n NOUN bracis-28402 96 8 \approx \approx PROPN bracis-28402 96 9 30000\ 30000\ PROPN bracis-28402 96 10 ) ) PUNCT bracis-28402 96 11 ) ) PUNCT bracis-28402 96 12 , , PUNCT bracis-28402 96 13 it it PRON bracis-28402 96 14 comprises comprise VERB bracis-28402 96 15 24 24 NUM bracis-28402 96 16 predictors predictor NOUN bracis-28402 96 17 , , PUNCT bracis-28402 96 18 comprising comprise VERB bracis-28402 96 19 fifteen fifteen NUM bracis-28402 96 20 numeric numeric ADJ bracis-28402 96 21 and and CCONJ bracis-28402 96 22 nine nine NUM bracis-28402 96 23 categorical categorical ADJ bracis-28402 96 24 variables variable NOUN bracis-28402 96 25 . . PUNCT bracis-28402 97 1 3 3 X bracis-28402 97 2 . . X bracis-28402 97 3 the the DET bracis-28402 97 4 heart heart NOUN bracis-28402 97 5 disease disease NOUN bracis-28402 97 6 dataset dataset VERB bracis-28402 97 7 [ [ X bracis-28402 97 8 10 10 NUM bracis-28402 97 9 ] ] PUNCT bracis-28402 97 10 ( ( PUNCT bracis-28402 97 11 heart heart NOUN bracis-28402 97 12 ) ) PUNCT bracis-28402 97 13 integrates integrate VERB bracis-28402 97 14 information information NOUN bracis-28402 97 15 from from ADP bracis-28402 97 16 four four NUM bracis-28402 97 17 databases database NOUN bracis-28402 97 18 : : PUNCT bracis-28402 97 19 cleveland cleveland PROPN bracis-28402 97 20 , , PUNCT bracis-28402 97 21 hungary hungary PROPN bracis-28402 97 22 , , PUNCT bracis-28402 97 23 switzerland switzerland PROPN bracis-28402 97 24 , , PUNCT bracis-28402 97 25 and and CCONJ bracis-28402 97 26 long long ADJ bracis-28402 97 27 beach beach NOUN bracis-28402 98 1 v. v. CCONJ bracis-28402 98 2 it it PRON bracis-28402 98 3 encompasses encompass VERB bracis-28402 98 4 76 76 NUM bracis-28402 98 5 attributes attribute NOUN bracis-28402 98 6 , , PUNCT bracis-28402 98 7 but but CCONJ bracis-28402 98 8 published publish VERB bracis-28402 98 9 experiments experiment NOUN bracis-28402 98 10 focus focus VERB bracis-28402 98 11 on on ADP bracis-28402 98 12 a a DET bracis-28402 98 13 subset subset NOUN bracis-28402 98 14 of of ADP bracis-28402 98 15 14 14 NUM bracis-28402 98 16 attributes attribute NOUN bracis-28402 98 17 . . PUNCT bracis-28402 99 1 the the DET bracis-28402 99 2 “ " PUNCT bracis-28402 99 3 target target NOUN bracis-28402 99 4 ” " PUNCT bracis-28402 99 5 field field NOUN bracis-28402 99 6 denotes denote VERB bracis-28402 99 7 the the DET bracis-28402 99 8 presence presence NOUN bracis-28402 99 9 of of ADP bracis-28402 99 10 heart heart NOUN bracis-28402 99 11 disease disease NOUN bracis-28402 99 12 in in ADP bracis-28402 99 13 patients patient NOUN bracis-28402 99 14 . . PUNCT bracis-28402 100 1 the the DET bracis-28402 100 2 dataset dataset NOUN bracis-28402 100 3 has have VERB bracis-28402 100 4 a a DET bracis-28402 100 5 sample sample NOUN bracis-28402 100 6 size size NOUN bracis-28402 100 7 of of ADP bracis-28402 100 8 \(n \(n NOUN bracis-28402 100 9 = = SYM bracis-28402 100 10 303\ 303\ NUM bracis-28402 100 11 ) ) PUNCT bracis-28402 100 12 and and CCONJ bracis-28402 100 13 includes include VERB bracis-28402 100 14 thirteen thirteen NUM bracis-28402 100 15 attributes attribute NOUN bracis-28402 100 16 , , PUNCT bracis-28402 100 17 of of ADP bracis-28402 100 18 which which PRON bracis-28402 100 19 five five NUM bracis-28402 100 20 are be AUX bracis-28402 100 21 numeric numeric ADJ bracis-28402 100 22 and and CCONJ bracis-28402 100 23 eight eight NUM bracis-28402 100 24 are be AUX bracis-28402 100 25 categorical categorical ADJ bracis-28402 100 26 . . PUNCT bracis-28402 101 1 4 4 X bracis-28402 101 2 . . X bracis-28402 101 3 the the DET bracis-28402 101 4 spambase spambase PROPN bracis-28402 101 5 data datum NOUN bracis-28402 101 6 set set VERB bracis-28402 101 7 [ [ X bracis-28402 101 8 9 9 NUM bracis-28402 101 9 ] ] X bracis-28402 101 10 ( ( PUNCT bracis-28402 101 11 spambase spambase NOUN bracis-28402 101 12 ) ) PUNCT bracis-28402 101 13 consists consist VERB bracis-28402 101 14 of of ADP bracis-28402 101 15 a a DET bracis-28402 101 16 sample sample NOUN bracis-28402 101 17 of of ADP bracis-28402 101 18 \(n \(n NOUN bracis-28402 101 19 = = SYM bracis-28402 101 20 4601\ 4601\ PROPN bracis-28402 101 21 ) ) PUNCT bracis-28402 101 22 emails email NOUN bracis-28402 101 23 classified classify VERB bracis-28402 101 24 as as ADP bracis-28402 101 25 either either PRON bracis-28402 101 26 “ " PUNCT bracis-28402 101 27 spam spam NOUN bracis-28402 101 28 ” " PUNCT bracis-28402 101 29 or or CCONJ bracis-28402 101 30 “ " PUNCT bracis-28402 101 31 non non ADJ bracis-28402 101 32 - - NOUN bracis-28402 101 33 spam spam NOUN bracis-28402 101 34 . . PUNCT bracis-28402 101 35 ” " PUNCT bracis-28402 102 1 it it PRON bracis-28402 102 2 contains contain VERB bracis-28402 102 3 fifty fifty NUM bracis-28402 102 4 - - PUNCT bracis-28402 102 5 seven seven NUM bracis-28402 102 6 numeric numeric ADJ bracis-28402 102 7 predictors predictor NOUN bracis-28402 102 8 , , PUNCT bracis-28402 102 9 including include VERB bracis-28402 102 10 metrics metric NOUN bracis-28402 102 11 such such ADJ bracis-28402 102 12 as as ADP bracis-28402 102 13 capital capital NOUN bracis-28402 102 14 character character NOUN bracis-28402 102 15 frequency frequency NOUN bracis-28402 102 16 and and CCONJ bracis-28402 102 17 the the DET bracis-28402 102 18 percentage percentage NOUN bracis-28402 102 19 of of ADP bracis-28402 102 20 matching matching NOUN bracis-28402 102 21 words word NOUN bracis-28402 102 22 . . PUNCT bracis-28402 103 1 the the DET bracis-28402 103 2 datasets dataset NOUN bracis-28402 103 3 are be AUX bracis-28402 103 4 preprocessed preprocesse VERB bracis-28402 103 5 by by ADP bracis-28402 103 6 converting convert VERB bracis-28402 103 7 categorical categorical ADJ bracis-28402 103 8 variables variable NOUN bracis-28402 103 9 to to ADP bracis-28402 103 10 numerical numerical ADJ bracis-28402 103 11 values value NOUN bracis-28402 103 12 using use VERB bracis-28402 103 13 labelencoder labelencoder NOUN bracis-28402 103 14 and and CCONJ bracis-28402 103 15 normalizing normalize VERB bracis-28402 103 16 the the DET bracis-28402 103 17 feature feature NOUN bracis-28402 103 18 values value NOUN bracis-28402 103 19 using use VERB bracis-28402 103 20 preprocessing preprocessing NOUN bracis-28402 103 21 normalize normalize NOUN bracis-28402 103 22 from from ADP bracis-28402 103 23 scikit scikit NOUN bracis-28402 103 24 - - PUNCT bracis-28402 103 25 learn learn NOUN bracis-28402 103 26 . . PUNCT bracis-28402 104 1 the the DET bracis-28402 104 2 preprocessed preprocesse VERB bracis-28402 104 3 data data NOUN bracis-28402 104 4 is be AUX bracis-28402 104 5 then then ADV bracis-28402 104 6 split split VERB bracis-28402 104 7 into into ADP bracis-28402 104 8 training training NOUN bracis-28402 104 9 and and CCONJ bracis-28402 104 10 testing testing NOUN bracis-28402 104 11 sets set NOUN bracis-28402 104 12 using use VERB bracis-28402 104 13 train_test_split train_test_split PROPN bracis-28402 104 14 from from ADP bracis-28402 104 15 scikit scikit NOUN bracis-28402 104 16 - - PUNCT bracis-28402 104 17 learn learn VERB bracis-28402 104 18 . . PUNCT bracis-28402 105 1 4.2 4.2 NUM bracis-28402 105 2 models model NOUN bracis-28402 105 3 and and CCONJ bracis-28402 105 4     SPACE bracis-28402 105 5 hyper hyper NOUN bracis-28402 105 6 - - NOUN bracis-28402 105 7 parameters parameter NOUN bracis-28402 105 8 the the DET bracis-28402 105 9 following follow VERB bracis-28402 105 10 models model NOUN bracis-28402 105 11 were be AUX bracis-28402 105 12 chosen choose VERB bracis-28402 105 13 for for ADP bracis-28402 105 14 the the DET bracis-28402 105 15 study study NOUN bracis-28402 105 16 : : PUNCT bracis-28402 105 17 random random ADJ bracis-28402 105 18 forest forest NOUN bracis-28402 105 19 classifier classifier NOUN bracis-28402 105 20 k k VERB bracis-28402 105 21 - - PUNCT bracis-28402 105 22 nearest near ADJ bracis-28402 105 23 neighbors neighbor NOUN bracis-28402 105 24 classifier classifier NOUN bracis-28402 105 25 decision decision NOUN bracis-28402 105 26 tree tree NOUN bracis-28402 105 27 classifier classifier NOUN bracis-28402 105 28 xgboost xgboost PROPN bracis-28402 105 29 classifier classifier VERB bracis-28402 105 30 the the DET bracis-28402 105 31 sampling sample VERB bracis-28402 105 32 functions function NOUN bracis-28402 105 33 used use VERB bracis-28402 105 34 in in ADP bracis-28402 105 35 the the DET bracis-28402 105 36 hyper hyper ADJ bracis-28402 105 37 - - ADJ bracis-28402 105 38 parameter parameter NOUN bracis-28402 105 39 mutation mutation NOUN bracis-28402 105 40 phase phase NOUN bracis-28402 105 41 are be AUX bracis-28402 105 42 denoted denote VERB bracis-28402 105 43 by by ADP bracis-28402 105 44 : : PUNCT bracis-28402 105 45 \(\mathcal \(\mathcal ADJ bracis-28402 105 46 { { PUNCT bracis-28402 105 47 s}_{[\mu s}_{[\mu PUNCT bracis-28402 105 48 _ _ PUNCT bracis-28402 105 49 1,\mu 1,\mu NUM bracis-28402 106 1 _ _ PUNCT bracis-28402 106 2 2,\min 2,\min NUM bracis-28402 106 3 ] ] SYM bracis-28402 106 4 } } PUNCT bracis-28402 106 5 \ \ NOUN bracis-28402 106 6 ): ): PUNCT bracis-28402 106 7 samples sample NOUN bracis-28402 106 8 from from ADP bracis-28402 106 9 a a DET bracis-28402 106 10 skellan skellan NOUN bracis-28402 106 11 distribution distribution NOUN bracis-28402 106 12 defined define VERB bracis-28402 106 13 with with ADP bracis-28402 106 14 \(\mu \(\mu PROPN bracis-28402 106 15 _ _ NOUN bracis-28402 106 16 1\ 1\ NUM bracis-28402 106 17 ) ) PUNCT bracis-28402 106 18 and and CCONJ bracis-28402 106 19 \(\mu \(\mu VERB bracis-28402 106 20 _ _ NOUN bracis-28402 106 21 2\ 2\ NUM bracis-28402 106 22 ) ) PUNCT bracis-28402 106 23 and and CCONJ bracis-28402 106 24 the the DET bracis-28402 106 25 center center NOUN bracis-28402 106 26 on on ADP bracis-28402 106 27 the the DET bracis-28402 106 28 current current ADJ bracis-28402 106 29 value value NOUN bracis-28402 106 30 of of ADP bracis-28402 106 31 the the DET bracis-28402 106 32 hyper hyper NOUN bracis-28402 106 33 - - NOUN bracis-28402 106 34 parameter parameter NOUN bracis-28402 106 35 . . PUNCT bracis-28402 107 1 the the DET bracis-28402 107 2 samples sample NOUN bracis-28402 107 3 truncated truncate VERB bracis-28402 107 4 to to ADP bracis-28402 107 5 \(\min \(\min VERB bracis-28402 107 6 \ \ NOUN bracis-28402 107 7 ) ) PUNCT bracis-28402 107 8 if if SCONJ bracis-28402 107 9 its its PRON bracis-28402 107 10 value value NOUN bracis-28402 107 11 is be AUX bracis-28402 107 12 below below ADV bracis-28402 107 13 \(\min \(\min PUNCT bracis-28402 107 14 \ \ NOUN bracis-28402 107 15 ) ) PUNCT bracis-28402 107 16 \(\mathcal \(\mathcal ADJ bracis-28402 107 17 { { PUNCT bracis-28402 107 18 n}_{[\sigma n}_{[\sigma NOUN bracis-28402 107 19 , , PUNCT bracis-28402 107 20 \min \min NOUN bracis-28402 107 21 , , PUNCT bracis-28402 107 22 \max \max PROPN bracis-28402 107 23 ] ] PUNCT bracis-28402 107 24 } } PUNCT bracis-28402 107 25 \ \ NOUN bracis-28402 107 26 ): ): PUNCT bracis-28402 107 27 samples sample NOUN bracis-28402 107 28 from from ADP bracis-28402 107 29 a a DET bracis-28402 107 30 normal normal ADJ bracis-28402 107 31 distribution distribution NOUN bracis-28402 107 32 defined define VERB bracis-28402 107 33 with with ADP bracis-28402 107 34 \(\mu \(\mu PROPN bracis-28402 107 35 \ \ NOUN bracis-28402 107 36 ) ) PUNCT bracis-28402 107 37 on on ADP bracis-28402 107 38 the the DET bracis-28402 107 39 current current ADJ bracis-28402 107 40 value value NOUN bracis-28402 107 41 of of ADP bracis-28402 107 42 the the DET bracis-28402 107 43 hyper hyper NOUN bracis-28402 107 44 - - NOUN bracis-28402 107 45 parameter parameter NOUN bracis-28402 107 46 and and CCONJ bracis-28402 107 47 \(\sigma \(\sigma NOUN bracis-28402 107 48 \ \ PROPN bracis-28402 107 49 ) ) PUNCT bracis-28402 107 50 . . PUNCT bracis-28402 108 1 the the DET bracis-28402 108 2 sample sample NOUN bracis-28402 108 3 is be AUX bracis-28402 108 4 truncated truncate VERB bracis-28402 108 5 to to ADP bracis-28402 108 6 \(\min \(\min VERB bracis-28402 108 7 \ \ NOUN bracis-28402 108 8 ) ) PUNCT bracis-28402 108 9 if if SCONJ bracis-28402 108 10 its its PRON bracis-28402 108 11 value value NOUN bracis-28402 108 12 is be AUX bracis-28402 108 13 below below ADV bracis-28402 108 14 \(\min \(\min PUNCT bracis-28402 109 1 \ \ NOUN bracis-28402 109 2 ) ) PUNCT bracis-28402 109 3 or or CCONJ bracis-28402 109 4 \(\max \(\max X bracis-28402 109 5 \ \ NOUN bracis-28402 109 6 ) ) PUNCT bracis-28402 109 7 if if SCONJ bracis-28402 109 8 its its PRON bracis-28402 109 9 value value NOUN bracis-28402 109 10 is be AUX bracis-28402 109 11 above above ADP bracis-28402 109 12 max max PROPN bracis-28402 109 13 \(\mathcal \(\mathcal X bracis-28402 109 14 { { PUNCT bracis-28402 109 15 u}_{[v_1,v_2, u}_{[v_1,v_2, PROPN bracis-28402 109 16 ... ... PUNCT bracis-28402 109 17 ,v_k]}\ ,v_k]}\ PUNCT bracis-28402 109 18 ): ): PUNCT bracis-28402 109 19 samples sample VERB bracis-28402 109 20 the the DET bracis-28402 109 21 values value NOUN bracis-28402 109 22 \(v_1,v_2, \(v_1,v_2, NOUN bracis-28402 109 23 ... ... PUNCT bracis-28402 109 24 ,v_k\ ,v_k\ PUNCT bracis-28402 109 25 ) ) PUNCT bracis-28402 109 26 using use VERB bracis-28402 109 27 a a DET bracis-28402 109 28 uniform uniform ADJ bracis-28402 109 29 distribution distribution NOUN bracis-28402 109 30 . . PUNCT bracis-28402 110 1 the the DET bracis-28402 110 2 hyper hyper NOUN bracis-28402 110 3 - - NOUN bracis-28402 110 4 parameters parameter NOUN bracis-28402 110 5 varied varied ADJ bracis-28402 110 6 in in ADP bracis-28402 110 7 each each DET bracis-28402 110 8 model model NOUN bracis-28402 110 9 and and CCONJ bracis-28402 110 10 the the DET bracis-28402 110 11 related related ADJ bracis-28402 110 12 sampling sampling NOUN bracis-28402 110 13 functions function NOUN bracis-28402 110 14 are be AUX bracis-28402 110 15 given give VERB bracis-28402 110 16 below below ADP bracis-28402 110 17 : : PUNCT bracis-28402 110 18 random random ADJ bracis-28402 110 19 forest forest NOUN bracis-28402 110 20 classifier classifier NOUN bracis-28402 110 21 : : PUNCT bracis-28402 110 22 number number NOUN bracis-28402 110 23 of of ADP bracis-28402 110 24 estimators estimator NOUN bracis-28402 110 25 : : PUNCT bracis-28402 110 26 \(\mathcal \(\mathcal ADJ bracis-28402 110 27 { { PUNCT bracis-28402 110 28 s}_{[10,10,3]}\ s}_{[10,10,3]}\ NOUN bracis-28402 110 29 ) ) PUNCT bracis-28402 110 30 maximum maximum ADJ bracis-28402 110 31 depth depth NOUN bracis-28402 110 32 : : PUNCT bracis-28402 110 33 \(\mathcal \(\mathcal ADJ bracis-28402 110 34 { { PUNCT bracis-28402 110 35 s}_{[2,2,2]}\ s}_{[2,2,2]}\ NOUN bracis-28402 110 36 ) ) PUNCT bracis-28402 110 37 maximum maximum ADJ bracis-28402 110 38 number number NOUN bracis-28402 110 39 of of ADP bracis-28402 110 40 features feature NOUN bracis-28402 110 41 : : PUNCT bracis-28402 110 42 \(\mathcal \(\mathcal ADJ bracis-28402 110 43 { { PUNCT bracis-28402 110 44 u}_{['sqrt u}_{['sqrt PROPN bracis-28402 110 45 ' ' NUM bracis-28402 110 46 , , PUNCT bracis-28402 110 47 ' ' PUNCT bracis-28402 110 48 log2 log2 PROPN bracis-28402 110 49 ' ' PUNCT bracis-28402 110 50 , , PUNCT bracis-28402 110 51 none]}\ none]}\ PROPN bracis-28402 110 52 ) ) PUNCT bracis-28402 110 53 k k NOUN bracis-28402 110 54 - - PUNCT bracis-28402 110 55 nearest near ADJ bracis-28402 110 56 neighbors neighbor NOUN bracis-28402 110 57 classifier classifier NOUN bracis-28402 110 58 : : PUNCT bracis-28402 110 59 number number NOUN bracis-28402 110 60 of of ADP bracis-28402 110 61 neighbors neighbor NOUN bracis-28402 110 62 : : PUNCT bracis-28402 110 63 \(\mathcal \(\mathcal ADJ bracis-28402 110 64 { { PUNCT bracis-28402 110 65 s}_{[1,1,3]}\ s}_{[1,1,3]}\ PROPN bracis-28402 110 66 ) ) PUNCT bracis-28402 110 67 weights weight NOUN bracis-28402 110 68 : : PUNCT bracis-28402 110 69 \(\mathcal \(\mathcal ADJ bracis-28402 110 70 { { PUNCT bracis-28402 110 71 u}_{['uniform u}_{['uniform PROPN bracis-28402 110 72 ' ' NUM bracis-28402 110 73 , , PUNCT bracis-28402 110 74 ' ' PUNCT bracis-28402 110 75 distance']}\ distance']}\ ADJ bracis-28402 110 76 ) ) PUNCT bracis-28402 110 77 decision decision NOUN bracis-28402 110 78 tree tree NOUN bracis-28402 110 79 classifier classifier NOUN bracis-28402 110 80 : : PUNCT bracis-28402 110 81 maximum maximum ADJ bracis-28402 110 82 depth depth NOUN bracis-28402 110 83 : : PUNCT bracis-28402 110 84 \(\mathcal \(\mathcal ADJ bracis-28402 110 85 { { PUNCT bracis-28402 110 86 s}_{[1,1,2]}\ s}_{[1,1,2]}\ PROPN bracis-28402 110 87 ) ) PUNCT bracis-28402 110 88 maximum maximum ADJ bracis-28402 110 89 number number NOUN bracis-28402 110 90 of of ADP bracis-28402 110 91 features feature NOUN bracis-28402 110 92 : : PUNCT bracis-28402 110 93 \(\mathcal \(\mathcal ADJ bracis-28402 110 94 { { PUNCT bracis-28402 110 95 u}_{['sqrt u}_{['sqrt PROPN bracis-28402 110 96 ' ' NUM bracis-28402 110 97 , , PUNCT bracis-28402 110 98 ' ' PUNCT bracis-28402 110 99 log2 log2 PROPN bracis-28402 110 100 ' ' PUNCT bracis-28402 110 101 , , PUNCT bracis-28402 110 102 none]}\ none]}\ PROPN bracis-28402 110 103 ) ) PUNCT bracis-28402 110 104 criterion criterion NOUN bracis-28402 110 105 : : PUNCT bracis-28402 110 106 \(\mathcal \(\mathcal ADJ bracis-28402 110 107 { { PUNCT bracis-28402 110 108 u}_{['gini u}_{['gini PROPN bracis-28402 110 109 ' ' NUM bracis-28402 110 110 , , PUNCT bracis-28402 110 111 ' ' PUNCT bracis-28402 110 112 entropy entropy PROPN bracis-28402 110 113 ' ' PUNCT bracis-28402 110 114 , , PUNCT bracis-28402 110 115 ' ' PUNCT bracis-28402 110 116 log\_loss']}\ log\_loss']}\ NOUN bracis-28402 110 117 ) ) PUNCT bracis-28402 110 118 xgboost xgboost NOUN bracis-28402 111 1 classifier classifier NOUN bracis-28402 111 2 : : PUNCT bracis-28402 111 3 tree tree NOUN bracis-28402 111 4 method method NOUN bracis-28402 111 5 : : PUNCT bracis-28402 111 6 \(\mathcal \(\mathcal ADJ bracis-28402 111 7 { { PUNCT bracis-28402 111 8 u}_{['auto u}_{['auto PROPN bracis-28402 111 9 ' ' NUM bracis-28402 111 10 , , PUNCT bracis-28402 111 11 ' ' PUNCT bracis-28402 111 12 exact exact ADJ bracis-28402 111 13 ' ' PUNCT bracis-28402 111 14 , , PUNCT bracis-28402 111 15 ' ' PUNCT bracis-28402 111 16 approx']}\ approx']}\ ADJ bracis-28402 111 17 ) ) PUNCT bracis-28402 111 18 maximum maximum ADJ bracis-28402 111 19 depth depth NOUN bracis-28402 111 20 : : PUNCT bracis-28402 111 21 \(\mathcal \(\mathcal ADJ bracis-28402 111 22 { { PUNCT bracis-28402 111 23 s}_{[1,1,1]}\ s}_{[1,1,1]}\ ADJ bracis-28402 111 24 ) ) PUNCT bracis-28402 111 25 booster booster NOUN bracis-28402 111 26 : : PUNCT bracis-28402 111 27 \(\mathcal \(\mathcal ADJ bracis-28402 111 28 { { PUNCT bracis-28402 111 29 u}_{['gbtree u}_{['gbtree PROPN bracis-28402 111 30 ' ' PUNCT bracis-28402 111 31 , , PUNCT bracis-28402 111 32 ' ' PUNCT bracis-28402 111 33 dart']}\ dart']}\ PROPN bracis-28402 111 34 ) ) PUNCT bracis-28402 111 35 number number NOUN bracis-28402 111 36 of of ADP bracis-28402 111 37 estimators estimator NOUN bracis-28402 111 38 : : PUNCT bracis-28402 111 39 \(\mathcal \(\mathcal ADJ bracis-28402 111 40 { { PUNCT bracis-28402 111 41 s}_{[1,1,1]}\ s}_{[1,1,1]}\ PROPN bracis-28402 111 42 ) ) PUNCT bracis-28402 111 43 subsample subsample NOUN bracis-28402 111 44 : : PUNCT bracis-28402 111 45 \(\mathcal \(\mathcal ADJ bracis-28402 111 46 { { PUNCT bracis-28402 111 47 n}_{[0.3,10 n}_{[0.3,10 NOUN bracis-28402 111 48 ^ ^ NOUN bracis-28402 111 49 -2,1]}\ -2,1]}\ NOUN bracis-28402 111 50 ) ) PUNCT bracis-28402 111 51 if if SCONJ bracis-28402 111 52 no no DET bracis-28402 111 53 sampling sample VERB bracis-28402 111 54 function function NOUN bracis-28402 111 55 is be AUX bracis-28402 111 56 the the DET bracis-28402 111 57 defined define VERB bracis-28402 111 58 , , PUNCT bracis-28402 111 59 the the DET bracis-28402 111 60 mutation mutation NOUN bracis-28402 111 61 selects select VERB bracis-28402 111 62 a a DET bracis-28402 111 63 random random ADJ bracis-28402 111 64 element element NOUN bracis-28402 111 65 from from ADP bracis-28402 111 66 the the DET bracis-28402 111 67 set set NOUN bracis-28402 111 68 of of ADP bracis-28402 111 69 possible possible ADJ bracis-28402 111 70 values value NOUN bracis-28402 111 71 . . PUNCT bracis-28402 112 1 otherwise otherwise ADV bracis-28402 112 2 , , PUNCT bracis-28402 112 3 it it PRON bracis-28402 112 4 ramdomly ramdomly ADV bracis-28402 112 5 samples sample NOUN bracis-28402 112 6 from from ADP bracis-28402 112 7 the the DET bracis-28402 112 8 defined define VERB bracis-28402 112 9 distribution distribution NOUN bracis-28402 112 10 . . PUNCT bracis-28402 113 1 the the DET bracis-28402 113 2 f1 f1 PROPN bracis-28402 113 3 score score NOUN bracis-28402 113 4 [ [ X bracis-28402 113 5 15 15 NUM bracis-28402 113 6 ] ] PUNCT bracis-28402 113 7 is be AUX bracis-28402 113 8 used use VERB bracis-28402 113 9 as as ADP bracis-28402 113 10 the the DET bracis-28402 113 11 evaluation evaluation NOUN bracis-28402 113 12 metric metric NOUN bracis-28402 113 13 for for ADP bracis-28402 113 14 the the DET bracis-28402 113 15 classification classification NOUN bracis-28402 113 16 models model NOUN bracis-28402 113 17 . . PUNCT bracis-28402 114 1 the the DET bracis-28402 114 2 f1 f1 PROPN bracis-28402 114 3 metric metric NOUN bracis-28402 114 4 is be AUX bracis-28402 114 5 a a DET bracis-28402 114 6 particular particular ADJ bracis-28402 114 7 case case NOUN bracis-28402 114 8 of of ADP bracis-28402 114 9 a a DET bracis-28402 114 10 general general ADJ bracis-28402 114 11 measure measure NOUN bracis-28402 114 12 \(f_{\beta \(f_{\beta ADJ bracis-28402 114 13 } } PUNCT bracis-28402 114 14 \ \ NOUN bracis-28402 114 15 ) ) PUNCT bracis-28402 114 16 . . PUNCT bracis-28402 115 1 this this DET bracis-28402 115 2 measure measure NOUN bracis-28402 115 3 is be AUX bracis-28402 115 4 a a DET bracis-28402 115 5 weighting weighting NOUN bracis-28402 115 6 between between ADP bracis-28402 115 7 precision precision NOUN bracis-28402 115 8 and and CCONJ bracis-28402 115 9 recall recall NOUN bracis-28402 115 10 , , PUNCT bracis-28402 115 11 indicated indicate VERB bracis-28402 115 12 in in ADP bracis-28402 115 13 cases case NOUN bracis-28402 115 14 of of ADP bracis-28402 115 15 unbalanced unbalanced ADJ bracis-28402 115 16 data datum NOUN bracis-28402 115 17 , , PUNCT bracis-28402 115 18 which which PRON bracis-28402 115 19 can can AUX bracis-28402 115 20 generate generate VERB bracis-28402 115 21 more more ADV bracis-28402 115 22 inaccurate inaccurate ADJ bracis-28402 115 23 results result NOUN bracis-28402 115 24 when when SCONJ bracis-28402 115 25 only only ADV bracis-28402 115 26 one one NUM bracis-28402 115 27 of of ADP bracis-28402 115 28 these these DET bracis-28402 115 29 two two NUM bracis-28402 115 30 measures measure NOUN bracis-28402 115 31 is be AUX bracis-28402 115 32 used use VERB bracis-28402 115 33 . . PUNCT bracis-28402 116 1 4.3 4.3 NUM bracis-28402 116 2 statistical statistical ADJ bracis-28402 116 3 tests test NOUN bracis-28402 116 4 the the DET bracis-28402 116 5 statistical statistical ADJ bracis-28402 116 6 tests test NOUN bracis-28402 116 7 used use VERB bracis-28402 116 8 by by ADP bracis-28402 116 9 algorithm algorithm NOUN bracis-28402 116 10     SPACE bracis-28402 116 11 1 1 NUM bracis-28402 116 12 to to PART bracis-28402 116 13 compare compare VERB bracis-28402 116 14 the the DET bracis-28402 116 15 performance performance NOUN bracis-28402 116 16 of of ADP bracis-28402 116 17 different different ADJ bracis-28402 116 18 hyper hyper NOUN bracis-28402 116 19 - - NOUN bracis-28402 116 20 parameters parameter NOUN bracis-28402 116 21 are be AUX bracis-28402 116 22 : : PUNCT bracis-28402 116 23 1 1 X bracis-28402 116 24 . . NUM bracis-28402 116 25 paired pair VERB bracis-28402 116 26 t t NOUN bracis-28402 116 27 - - PUNCT bracis-28402 116 28 test test NOUN bracis-28402 116 29 for for ADP bracis-28402 116 30 two two NUM bracis-28402 116 31 related related ADJ bracis-28402 116 32 samples sample NOUN bracis-28402 116 33 ( ( PUNCT bracis-28402 116 34 ttest_rel ttest_rel NOUN bracis-28402 116 35 ) ) PUNCT bracis-28402 116 36 2 2 NUM bracis-28402 116 37 . . X bracis-28402 116 38 two two NUM bracis-28402 116 39 - - PUNCT bracis-28402 116 40 sample sample NOUN bracis-28402 116 41 t t NOUN bracis-28402 116 42 - - PUNCT bracis-28402 116 43 test test NOUN bracis-28402 116 44 ( ( PUNCT bracis-28402 116 45 ttest_in ttest_in PROPN bracis-28402 116 46 ) ) PUNCT bracis-28402 116 47 3 3 NUM bracis-28402 116 48 . . X bracis-28402 116 49 mann mann PROPN bracis-28402 116 50 - - PUNCT bracis-28402 116 51 whitney whitney PROPN bracis-28402 116 52 u u PROPN bracis-28402 116 53 test test NOUN bracis-28402 116 54 ( ( PUNCT bracis-28402 116 55 mannwhitneyu mannwhitneyu NOUN bracis-28402 116 56 ) ) PUNCT bracis-28402 116 57 they they PRON bracis-28402 116 58 are be AUX bracis-28402 116 59 performed perform VERB bracis-28402 116 60 on on ADP bracis-28402 116 61 the the DET bracis-28402 116 62 set set NOUN bracis-28402 116 63 of of ADP bracis-28402 116 64 evaluation evaluation NOUN bracis-28402 116 65 metrics metric NOUN bracis-28402 116 66 collected collect VERB bracis-28402 116 67 using use VERB bracis-28402 116 68 k k ADJ bracis-28402 116 69 - - ADJ bracis-28402 116 70 fold fold ADJ bracis-28402 116 71 cross cross NOUN bracis-28402 116 72 - - NOUN bracis-28402 116 73 validation validation NOUN bracis-28402 116 74 . . PUNCT bracis-28402 117 1 as as ADP bracis-28402 117 2 baseline baseline NOUN bracis-28402 117 3 , , PUNCT bracis-28402 117 4 algorithm algorithm PROPN bracis-28402 117 5     SPACE bracis-28402 117 6 1 1 NUM bracis-28402 117 7 was be AUX bracis-28402 117 8 also also ADV bracis-28402 117 9 without without ADP bracis-28402 117 10 any any DET bracis-28402 117 11 statistical statistical ADJ bracis-28402 117 12 test test NOUN bracis-28402 117 13 . . PUNCT bracis-28402 118 1 in in ADP bracis-28402 118 2 this this DET bracis-28402 118 3 case case NOUN bracis-28402 118 4 is be AUX bracis-28402 118 5 simply simply ADV bracis-28402 118 6 selects select VERB bracis-28402 118 7 the the DET bracis-28402 118 8 models model NOUN bracis-28402 118 9 with with ADP bracis-28402 118 10 the the DET bracis-28402 118 11 best good ADJ bracis-28402 118 12 average average ADJ bracis-28402 118 13 performance performance NOUN bracis-28402 118 14 as as SCONJ bracis-28402 118 15 given give VERB bracis-28402 118 16 by by ADP bracis-28402 118 17 the the DET bracis-28402 118 18 cross cross ADJ bracis-28402 118 19 - - ADJ bracis-28402 118 20 validation validation ADJ bracis-28402 118 21 procedure procedure NOUN bracis-28402 118 22 . . PUNCT bracis-28402 119 1 this this DET bracis-28402 119 2 procedure procedure NOUN bracis-28402 119 3 will will AUX bracis-28402 119 4 be be AUX bracis-28402 119 5 called call VERB bracis-28402 119 6 dummy_stats_test dummy_stats_t ADJ bracis-28402 119 7 for for ADP bracis-28402 119 8 rest rest NOUN bracis-28402 119 9 of of ADP bracis-28402 119 10 the the DET bracis-28402 119 11 text text NOUN bracis-28402 119 12 . . PUNCT bracis-28402 120 1 4.4 4.4 NUM bracis-28402 120 2 experimental experimental ADJ bracis-28402 120 3 procedure procedure NOUN bracis-28402 120 4 algorithm algorithm NOUN bracis-28402 120 5     SPACE bracis-28402 120 6 1 1 NUM bracis-28402 120 7 was be AUX bracis-28402 120 8 executed execute VERB bracis-28402 120 9 10 10 NUM bracis-28402 120 10 independent independent ADJ bracis-28402 120 11 times time NOUN bracis-28402 120 12 for for ADP bracis-28402 120 13 each each DET bracis-28402 120 14 combination combination NOUN bracis-28402 120 15 of of ADP bracis-28402 120 16 the the DET bracis-28402 120 17 following follow VERB bracis-28402 120 18 factor factor NOUN bracis-28402 120 19 levels level NOUN bracis-28402 120 20 : : PUNCT bracis-28402 121 1 datasets dataset NOUN bracis-28402 121 2 : : PUNCT bracis-28402 121 3 [ [ X bracis-28402 121 4 banking banking NOUN bracis-28402 121 5 , , PUNCT bracis-28402 121 6 credit credit NOUN bracis-28402 121 7 , , PUNCT bracis-28402 121 8 heart heart NOUN bracis-28402 121 9 , , PUNCT bracis-28402 121 10 spambase spambase NOUN bracis-28402 121 11 ] ] PUNCT bracis-28402 121 12 statistical statistical ADJ bracis-28402 121 13 tests test NOUN bracis-28402 121 14 : : PUNCT bracis-28402 122 1 [ [ X bracis-28402 122 2 paired pair VERB bracis-28402 122 3 t t NOUN bracis-28402 122 4 - - PUNCT bracis-28402 122 5 test test NOUN bracis-28402 122 6 for for ADP bracis-28402 122 7 two two NUM bracis-28402 122 8 related related ADJ bracis-28402 122 9 samples sample NOUN bracis-28402 122 10 ( ( PUNCT bracis-28402 122 11 ttest_rel ttest_rel NOUN bracis-28402 122 12 ) ) PUNCT bracis-28402 122 13 , , PUNCT bracis-28402 122 14 two two NUM bracis-28402 122 15 - - PUNCT bracis-28402 122 16 sample sample NOUN bracis-28402 122 17 t t NOUN bracis-28402 122 18 - - PUNCT bracis-28402 122 19 test test NOUN bracis-28402 122 20 ( ( PUNCT bracis-28402 122 21 ttest_in ttest_in PROPN bracis-28402 122 22 ) ) PUNCT bracis-28402 122 23 , , PUNCT bracis-28402 122 24 mann mann PROPN bracis-28402 122 25 - - PUNCT bracis-28402 122 26 whitney whitney PROPN bracis-28402 122 27 u u PROPN bracis-28402 122 28 test test NOUN bracis-28402 122 29 ( ( PUNCT bracis-28402 122 30 mannwhitneyu mannwhitneyu NOUN bracis-28402 122 31 ) ) PUNCT bracis-28402 122 32 , , PUNCT bracis-28402 122 33 dummy dummy NOUN bracis-28402 122 34 ( ( PUNCT bracis-28402 122 35 dummy_stats_test dummy_stats_test X bracis-28402 122 36 ) ) PUNCT bracis-28402 122 37 ] ] PUNCT bracis-28402 123 1 k k X bracis-28402 123 2 folds fold NOUN bracis-28402 123 3 : : PUNCT bracis-28402 124 1 [ [ X bracis-28402 124 2 10 10 NUM bracis-28402 124 3 , , PUNCT bracis-28402 124 4 30 30 NUM bracis-28402 124 5 , , PUNCT bracis-28402 124 6 50 50 NUM bracis-28402 124 7 ] ] SYM bracis-28402 124 8 number number NOUN bracis-28402 124 9 of of ADP bracis-28402 124 10 generations generation NOUN bracis-28402 124 11 : : PUNCT bracis-28402 125 1 [ [ X bracis-28402 125 2 25 25 NUM bracis-28402 125 3 , , PUNCT bracis-28402 125 4 100 100 NUM bracis-28402 125 5 , , PUNCT bracis-28402 125 6 1000 1000 NUM bracis-28402 125 7 ] ] SYM bracis-28402 125 8 5 5 NUM bracis-28402 125 9 results result VERB bracis-28402 125 10 this this DET bracis-28402 125 11 section section NOUN bracis-28402 125 12 summarizes summarize VERB bracis-28402 125 13 the the DET bracis-28402 125 14 results result NOUN bracis-28402 125 15 obtained obtain VERB bracis-28402 125 16 using use VERB bracis-28402 125 17 algorithm algorithm NOUN bracis-28402 125 18     SPACE bracis-28402 125 19 1 1 NUM bracis-28402 125 20 for for ADP bracis-28402 125 21 all all DET bracis-28402 125 22 tested test VERB bracis-28402 125 23 conditions condition NOUN bracis-28402 125 24 related relate VERB bracis-28402 125 25 to to ADP bracis-28402 125 26 the the DET bracis-28402 125 27 research research NOUN bracis-28402 125 28 questions question NOUN bracis-28402 125 29 in in ADP bracis-28402 125 30 sect sect NOUN bracis-28402 125 31 . . PUNCT bracis-28402 125 32     SPACE bracis-28402 126 1 1 1 X bracis-28402 126 2 . . PUNCT bracis-28402 127 1 the the DET bracis-28402 127 2 results result NOUN bracis-28402 127 3 are be AUX bracis-28402 127 4 presented present VERB bracis-28402 127 5 as as ADP bracis-28402 127 6 the the DET bracis-28402 127 7 percentage percentage NOUN bracis-28402 127 8 improvement improvement NOUN bracis-28402 127 9 in in ADP bracis-28402 127 10 performance performance NOUN bracis-28402 127 11 between between ADP bracis-28402 127 12 the the DET bracis-28402 127 13 final final ADJ bracis-28402 127 14 best good ADJ bracis-28402 127 15 model model NOUN bracis-28402 127 16 ( ( PUNCT bracis-28402 127 17 \(f1_{final}\ \(f1_{final}\ NUM bracis-28402 127 18 ) ) PUNCT bracis-28402 127 19 ) ) PUNCT bracis-28402 127 20 and and CCONJ bracis-28402 127 21 the the DET bracis-28402 127 22 initial initial ADJ bracis-28402 127 23 best good ADJ bracis-28402 127 24 model model NOUN bracis-28402 127 25 ( ( PUNCT bracis-28402 127 26 \(f1_0\ \(f1_0\ NOUN bracis-28402 127 27 ) ) PUNCT bracis-28402 127 28 ) ) PUNCT bracis-28402 127 29 which which PRON bracis-28402 127 30 was be AUX bracis-28402 127 31 computed compute VERB bracis-28402 127 32 by by ADP bracis-28402 127 33 the the DET bracis-28402 127 34 equation equation NOUN bracis-28402 127 35 below below ADV bracis-28402 127 36 : : PUNCT bracis-28402 127 37 $ $ SYM bracis-28402 127 38 $ $ SYM bracis-28402 127 39 \begin{aligned \begin{aligne VERB bracis-28402 127 40 } } PUNCT bracis-28402 127 41 \text \text ADP bracis-28402 127 42 { { PUNCT bracis-28402 127 43 \%improvement \%improvement ADJ bracis-28402 127 44 } } PUNCT bracis-28402 127 45 = = SYM bracis-28402 127 46 \frac{f1_{final \frac{f1_{final ADJ bracis-28402 127 47 } } PUNCT bracis-28402 127 48 f1_0}{f1_0 f1_0}{f1_0 PROPN bracis-28402 127 49 } } PUNCT bracis-28402 127 50 \end{aligned}$$ \end{aligned}$$ X bracis-28402 127 51 ( ( PUNCT bracis-28402 127 52 6 6 NUM bracis-28402 127 53 ) ) PUNCT bracis-28402 127 54 5.1 5.1 NUM bracis-28402 127 55 performance performance NOUN bracis-28402 127 56 over over ADP bracis-28402 127 57     SPACE bracis-28402 127 58 datasets dataset NOUN bracis-28402 127 59 figure figure VERB bracis-28402 127 60     SPACE bracis-28402 127 61 1 1 NUM bracis-28402 127 62 shows show VERB bracis-28402 127 63 the the DET bracis-28402 127 64 box box NOUN bracis-28402 127 65 - - PUNCT bracis-28402 127 66 plots plot NOUN bracis-28402 127 67 for for ADP bracis-28402 127 68 the the DET bracis-28402 127 69 \(\%improvement\ \(\%improvement\ PROPN bracis-28402 127 70 ) ) PUNCT bracis-28402 127 71 obtained obtain VERB bracis-28402 127 72 with with ADP bracis-28402 127 73 algorithm algorithm NOUN bracis-28402 127 74     SPACE bracis-28402 127 75 1 1 NUM bracis-28402 127 76 combining combine VERB bracis-28402 127 77 all all DET bracis-28402 127 78 the the DET bracis-28402 127 79 possible possible ADJ bracis-28402 127 80 configurations configuration NOUN bracis-28402 127 81 . . PUNCT bracis-28402 128 1 it it PRON bracis-28402 128 2 can can AUX bracis-28402 128 3 be be AUX bracis-28402 128 4 seen see VERB bracis-28402 128 5 that that SCONJ bracis-28402 128 6 the the DET bracis-28402 128 7 proposed propose VERB bracis-28402 128 8 procedure procedure NOUN bracis-28402 128 9 was be AUX bracis-28402 128 10 more more ADV bracis-28402 128 11 successful successful ADJ bracis-28402 128 12 for for SCONJ bracis-28402 128 13 the the DET bracis-28402 128 14 spambase spambase NOUN bracis-28402 128 15 dataset dataset VERB bracis-28402 128 16 with with ADP bracis-28402 128 17 an an DET bracis-28402 128 18 average average ADJ bracis-28402 128 19 improvement improvement NOUN bracis-28402 128 20 around around ADP bracis-28402 128 21 7 7 NUM bracis-28402 128 22 % % NOUN bracis-28402 128 23 reaching reach VERB bracis-28402 128 24 17.5 17.5 NUM bracis-28402 128 25 % % NOUN bracis-28402 128 26 improvement improvement NOUN bracis-28402 128 27 in in ADP bracis-28402 128 28 some some DET bracis-28402 128 29 scenarios scenario NOUN bracis-28402 128 30 . . PUNCT bracis-28402 129 1 conversely conversely ADV bracis-28402 129 2 , , PUNCT bracis-28402 129 3 the the DET bracis-28402 129 4 improvements improvement NOUN bracis-28402 129 5 obtained obtain VERB bracis-28402 129 6 for for ADP bracis-28402 129 7 the the DET bracis-28402 129 8 other other ADJ bracis-28402 129 9 datasets dataset NOUN bracis-28402 129 10 were be AUX bracis-28402 129 11 more more ADV bracis-28402 129 12 modest modest ADJ bracis-28402 129 13 with with ADP bracis-28402 129 14 averages average NOUN bracis-28402 129 15 around around ADP bracis-28402 129 16 3 3 NUM bracis-28402 129 17 % % NOUN bracis-28402 129 18 , , PUNCT bracis-28402 129 19 1.7 1.7 NUM bracis-28402 129 20 % % NOUN bracis-28402 129 21 and and CCONJ bracis-28402 129 22 2.6 2.6 NUM bracis-28402 129 23 % % NOUN bracis-28402 129 24 for for ADP bracis-28402 129 25 the the DET bracis-28402 129 26 banking banking NOUN bracis-28402 129 27 , , PUNCT bracis-28402 129 28 credit credit NOUN bracis-28402 129 29 and and CCONJ bracis-28402 129 30 heart heart NOUN bracis-28402 129 31 datasets dataset NOUN bracis-28402 129 32 , , PUNCT bracis-28402 129 33 respectively respectively ADV bracis-28402 129 34 . . PUNCT bracis-28402 130 1 fig fig NOUN bracis-28402 130 2 . . PUNCT bracis-28402 131 1 1 1 NUM bracis-28402 131 2 . . X bracis-28402 131 3 % % NOUN bracis-28402 131 4 of of ADP bracis-28402 131 5 improvement improvement NOUN bracis-28402 131 6 by by ADP bracis-28402 131 7 dataset dataset ADJ bracis-28402 131 8 full full ADJ bracis-28402 131 9 size size NOUN bracis-28402 131 10 image image NOUN bracis-28402 131 11 5.2 5.2 NUM bracis-28402 131 12 performance performance NOUN bracis-28402 131 13 of of ADP bracis-28402 131 14     SPACE bracis-28402 131 15 the the DET bracis-28402 131 16     SPACE bracis-28402 131 17 statistical statistical ADJ bracis-28402 131 18 tests test NOUN bracis-28402 131 19 varying vary VERB bracis-28402 131 20 number number NOUN bracis-28402 131 21 of of ADP bracis-28402 131 22     SPACE bracis-28402 131 23 folds fold NOUN bracis-28402 131 24 figure figure NOUN bracis-28402 131 25     SPACE bracis-28402 131 26 2 2 NUM bracis-28402 131 27 shows show VERB bracis-28402 131 28 the the DET bracis-28402 131 29 box box NOUN bracis-28402 131 30 - - PUNCT bracis-28402 131 31 plots plot NOUN bracis-28402 131 32 for for ADP bracis-28402 131 33 the the DET bracis-28402 131 34 \(\%improvement\ \(\%improvement\ PROPN bracis-28402 131 35 ) ) PUNCT bracis-28402 131 36 obtained obtain VERB bracis-28402 131 37 with with ADP bracis-28402 131 38 algorithm algorithm NOUN bracis-28402 131 39     SPACE bracis-28402 131 40 1 1 NUM bracis-28402 131 41 when when SCONJ bracis-28402 131 42 we we PRON bracis-28402 131 43 vary vary VERB bracis-28402 131 44 the the DET bracis-28402 131 45 applied apply VERB bracis-28402 131 46 statistical statistical ADJ bracis-28402 131 47 test test NOUN bracis-28402 131 48 and and CCONJ bracis-28402 131 49 the the DET bracis-28402 131 50 number number NOUN bracis-28402 131 51 of of ADP bracis-28402 131 52 folds fold NOUN bracis-28402 131 53 used use VERB bracis-28402 131 54 in in ADP bracis-28402 131 55 the the DET bracis-28402 131 56 cross cross ADJ bracis-28402 131 57 - - ADJ bracis-28402 131 58 validations validation NOUN bracis-28402 131 59 procedure procedure NOUN bracis-28402 131 60 . . PUNCT bracis-28402 132 1 it it PRON bracis-28402 132 2 can can AUX bracis-28402 132 3 be be AUX bracis-28402 132 4 seen see VERB bracis-28402 132 5 that that SCONJ bracis-28402 132 6 , , PUNCT bracis-28402 132 7 in in ADP bracis-28402 132 8 this this DET bracis-28402 132 9 scenario scenario NOUN bracis-28402 132 10 where where SCONJ bracis-28402 132 11 the the DET bracis-28402 132 12 dataset dataset NOUN bracis-28402 132 13 effect effect NOUN bracis-28402 132 14 is be AUX bracis-28402 132 15 confounded confound VERB bracis-28402 132 16 increasing increase VERB bracis-28402 132 17 the the DET bracis-28402 132 18 number number NOUN bracis-28402 132 19 of of ADP bracis-28402 132 20 folds fold NOUN bracis-28402 132 21 had have VERB bracis-28402 132 22 no no DET bracis-28402 132 23 effect effect NOUN bracis-28402 132 24 in in ADP bracis-28402 132 25 the the DET bracis-28402 132 26 \(\%improvement\ \(\%improvement\ PROPN bracis-28402 132 27 ) ) PUNCT bracis-28402 132 28 . . PUNCT bracis-28402 133 1 fig fig NOUN bracis-28402 133 2 . . PUNCT bracis-28402 134 1 2 2 NUM bracis-28402 134 2 . . X bracis-28402 134 3 % % NOUN bracis-28402 134 4 of of ADP bracis-28402 134 5 improvement improvement NOUN bracis-28402 134 6 by by ADP bracis-28402 134 7 statistical statistical ADJ bracis-28402 134 8 test test NOUN bracis-28402 134 9 varying vary VERB bracis-28402 134 10 the the DET bracis-28402 134 11 number number NOUN bracis-28402 134 12 of of ADP bracis-28402 134 13 folds fold NOUN bracis-28402 134 14 full full ADJ bracis-28402 134 15 size size NOUN bracis-28402 134 16 image image NOUN bracis-28402 134 17 figure figure NOUN bracis-28402 134 18     SPACE bracis-28402 134 19 3 3 NUM bracis-28402 134 20 presents present VERB bracis-28402 134 21 the the DET bracis-28402 134 22 factors factor NOUN bracis-28402 134 23 from from ADP bracis-28402 134 24 fig fig NOUN bracis-28402 134 25 . . PUNCT bracis-28402 134 26     SPACE bracis-28402 134 27 2 2 NUM bracis-28402 134 28 for for ADP bracis-28402 134 29 each each DET bracis-28402 134 30 dataset dataset NOUN bracis-28402 134 31 , , PUNCT bracis-28402 134 32 separately separately ADV bracis-28402 134 33 . . PUNCT bracis-28402 135 1 looking look VERB bracis-28402 135 2 at at ADP bracis-28402 135 3 the the DET bracis-28402 135 4 spambase spambase NOUN bracis-28402 135 5 results result NOUN bracis-28402 135 6 , , PUNCT bracis-28402 135 7 the the DET bracis-28402 135 8 dataset dataset NOUN bracis-28402 135 9 where where SCONJ bracis-28402 135 10 algorithm algorithm NOUN bracis-28402 135 11     SPACE bracis-28402 135 12 1 1 NUM bracis-28402 135 13 performed perform VERB bracis-28402 135 14 the the DET bracis-28402 135 15 set set NOUN bracis-28402 135 16 , , PUNCT bracis-28402 135 17 it it PRON bracis-28402 135 18 can can AUX bracis-28402 135 19 be be AUX bracis-28402 135 20 seen see VERB bracis-28402 135 21 that that SCONJ bracis-28402 135 22 , , PUNCT bracis-28402 135 23 even even ADV bracis-28402 135 24 though though SCONJ bracis-28402 135 25 there there PRON bracis-28402 135 26 is be VERB bracis-28402 135 27 still still ADV bracis-28402 135 28 no no DET bracis-28402 135 29 significant significant ADJ bracis-28402 135 30 difference difference NOUN bracis-28402 135 31 in in ADP bracis-28402 135 32 the the DET bracis-28402 135 33 average average ADJ bracis-28402 135 34 \(\%improvement\ \(\%improvement\ PROPN bracis-28402 135 35 ) ) PUNCT bracis-28402 135 36 , , PUNCT bracis-28402 135 37 increasing increase VERB bracis-28402 135 38 the the DET bracis-28402 135 39 number number NOUN bracis-28402 135 40 of of ADP bracis-28402 135 41 folds fold NOUN bracis-28402 135 42 contributed contribute VERB bracis-28402 135 43 to to PART bracis-28402 135 44 reduce reduce VERB bracis-28402 135 45 the the DET bracis-28402 135 46 variance variance NOUN bracis-28402 135 47 of of ADP bracis-28402 135 48 the the DET bracis-28402 135 49 results result NOUN bracis-28402 135 50 for for ADP bracis-28402 135 51 the the DET bracis-28402 135 52 parametric parametric ADJ bracis-28402 135 53 tests test NOUN bracis-28402 135 54 . . PUNCT bracis-28402 136 1 this this DET bracis-28402 136 2 phenomenon phenomenon NOUN bracis-28402 136 3 , , PUNCT bracis-28402 136 4 however however ADV bracis-28402 136 5 , , PUNCT bracis-28402 136 6 could could AUX bracis-28402 136 7 not not PART bracis-28402 136 8 be be AUX bracis-28402 136 9 observed observe VERB bracis-28402 136 10 in in ADP bracis-28402 136 11 the the DET bracis-28402 136 12 overall overall ADJ bracis-28402 136 13 results result NOUN bracis-28402 136 14 , , PUNCT bracis-28402 136 15 possibly possibly ADV bracis-28402 136 16 because because SCONJ bracis-28402 136 17 of of ADP bracis-28402 136 18 the the DET bracis-28402 136 19 difficulty difficulty NOUN bracis-28402 136 20 algorithm algorithm NOUN bracis-28402 136 21     SPACE bracis-28402 136 22 1 1 NUM bracis-28402 136 23 had have VERB bracis-28402 136 24 to to PART bracis-28402 136 25 generate generate VERB bracis-28402 136 26 improved improved ADJ bracis-28402 136 27 models model NOUN bracis-28402 136 28 . . PUNCT bracis-28402 137 1 fig fig NOUN bracis-28402 137 2 . . PUNCT bracis-28402 138 1 3 3 X bracis-28402 138 2 . . X bracis-28402 138 3 % % NOUN bracis-28402 138 4 of of ADP bracis-28402 138 5 improvement improvement NOUN bracis-28402 138 6 by by ADP bracis-28402 138 7 statistical statistical ADJ bracis-28402 138 8 test test NOUN bracis-28402 138 9 varying vary VERB bracis-28402 138 10 the the DET bracis-28402 138 11 number number NOUN bracis-28402 138 12 of of ADP bracis-28402 138 13 folds fold NOUN bracis-28402 138 14 for for SCONJ bracis-28402 138 15 each each DET bracis-28402 138 16 dataset dataset VERB bracis-28402 138 17 full full ADJ bracis-28402 138 18 size size NOUN bracis-28402 138 19 image image NOUN bracis-28402 138 20 5.3 5.3 NUM bracis-28402 138 21 performance performance NOUN bracis-28402 138 22 of of ADP bracis-28402 138 23     SPACE bracis-28402 138 24 the the DET bracis-28402 138 25     SPACE bracis-28402 138 26 statistical statistical ADJ bracis-28402 138 27 tests test NOUN bracis-28402 138 28 varying vary VERB bracis-28402 138 29 the the DET bracis-28402 138 30     SPACE bracis-28402 138 31 maximum maximum ADJ bracis-28402 138 32 number number NOUN bracis-28402 138 33 of of ADP bracis-28402 138 34     SPACE bracis-28402 138 35 generations generation NOUN bracis-28402 138 36 figure figure VERB bracis-28402 138 37     SPACE bracis-28402 138 38 4 4 NUM bracis-28402 138 39 displays display VERB bracis-28402 138 40 the the DET bracis-28402 138 41 performance performance NOUN bracis-28402 138 42 algorithm algorithm NOUN bracis-28402 138 43     SPACE bracis-28402 138 44 1 1 NUM bracis-28402 138 45 in in ADP bracis-28402 138 46 regards regard NOUN bracis-28402 138 47 to to ADP bracis-28402 138 48 the the DET bracis-28402 138 49 \(\%improvemnt\ \(\%improvemnt\ NUM bracis-28402 138 50 ) ) PUNCT bracis-28402 138 51 when when SCONJ bracis-28402 138 52 varying vary VERB bracis-28402 138 53 the the DET bracis-28402 138 54 statistical statistical ADJ bracis-28402 138 55 test test NOUN bracis-28402 138 56 and and CCONJ bracis-28402 138 57 the the DET bracis-28402 138 58 maximum maximum ADJ bracis-28402 138 59 number number NOUN bracis-28402 138 60 of of ADP bracis-28402 138 61 generations generation NOUN bracis-28402 138 62 ( ( PUNCT bracis-28402 138 63 iterations iteration NOUN bracis-28402 138 64 ) ) PUNCT bracis-28402 138 65 allowed allow VERB bracis-28402 138 66 . . PUNCT bracis-28402 139 1 as as SCONJ bracis-28402 139 2 expected expect VERB bracis-28402 139 3 , , PUNCT bracis-28402 139 4 when when SCONJ bracis-28402 139 5 the the DET bracis-28402 139 6 number number NOUN bracis-28402 139 7 of of ADP bracis-28402 139 8 generations generation NOUN bracis-28402 139 9 increases increase VERB bracis-28402 139 10 the the DET bracis-28402 139 11 \(\%improvement\ \(\%improvement\ NOUN bracis-28402 139 12 ) ) PUNCT bracis-28402 139 13 also also ADV bracis-28402 139 14 increases increase VERB bracis-28402 139 15 . . PUNCT bracis-28402 140 1 these these DET bracis-28402 140 2 overall overall ADJ bracis-28402 140 3 results result NOUN bracis-28402 140 4 do do AUX bracis-28402 140 5 not not PART bracis-28402 140 6 show show VERB bracis-28402 140 7 an an DET bracis-28402 140 8 interaction interaction NOUN bracis-28402 140 9 between between ADP bracis-28402 140 10 the the DET bracis-28402 140 11 statistical statistical ADJ bracis-28402 140 12 test test NOUN bracis-28402 140 13 and and CCONJ bracis-28402 140 14 the the DET bracis-28402 140 15 number number NOUN bracis-28402 140 16 of of ADP bracis-28402 140 17 iterations iteration NOUN bracis-28402 140 18 since since SCONJ bracis-28402 140 19 the the DET bracis-28402 140 20 difference difference NOUN bracis-28402 140 21 in in ADP bracis-28402 140 22 the the DET bracis-28402 140 23 performance performance NOUN bracis-28402 140 24 among among ADP bracis-28402 140 25 the the DET bracis-28402 140 26 different different ADJ bracis-28402 140 27 statistical statistical ADJ bracis-28402 140 28 tests test NOUN bracis-28402 140 29 and and CCONJ bracis-28402 140 30 the the DET bracis-28402 140 31 dummy dummy ADJ bracis-28402 140 32 test test NOUN bracis-28402 140 33 remains remain VERB bracis-28402 140 34 almost almost ADV bracis-28402 140 35 constant constant ADJ bracis-28402 140 36 as as ADP bracis-28402 140 37 the the DET bracis-28402 140 38 number number NOUN bracis-28402 140 39 o o NOUN bracis-28402 140 40 generations generation NOUN bracis-28402 140 41 increases increase NOUN bracis-28402 140 42 . . PUNCT bracis-28402 141 1 fig fig NOUN bracis-28402 141 2 . . PUNCT bracis-28402 142 1 4 4 X bracis-28402 142 2 . . X bracis-28402 142 3 % % NOUN bracis-28402 142 4 of of ADP bracis-28402 142 5 improvement improvement NOUN bracis-28402 142 6 by by ADP bracis-28402 142 7 statistical statistical ADJ bracis-28402 142 8 test test NOUN bracis-28402 142 9 and and CCONJ bracis-28402 142 10 maximum maximum ADJ bracis-28402 142 11 number number NOUN bracis-28402 142 12 of of ADP bracis-28402 142 13 generations generation NOUN bracis-28402 142 14 full full ADJ bracis-28402 142 15 size size NOUN bracis-28402 142 16 image image NOUN bracis-28402 142 17 figure figure NOUN bracis-28402 142 18     SPACE bracis-28402 142 19 5 5 NUM bracis-28402 142 20 displays display VERB bracis-28402 142 21 the the DET bracis-28402 142 22 performance performance NOUN bracis-28402 142 23 algorithm algorithm NOUN bracis-28402 142 24     SPACE bracis-28402 142 25 1 1 NUM bracis-28402 142 26 in in ADP bracis-28402 142 27 regards regard NOUN bracis-28402 142 28 to to ADP bracis-28402 142 29 the the DET bracis-28402 142 30 \(\%improvemnt\ \(\%improvemnt\ NUM bracis-28402 142 31 ) ) PUNCT bracis-28402 142 32 for for ADP bracis-28402 142 33 each each DET bracis-28402 142 34 dataset dataset NOUN bracis-28402 142 35 . . PUNCT bracis-28402 143 1 for for ADP bracis-28402 143 2 the the DET bracis-28402 143 3 datasets dataset NOUN bracis-28402 143 4 heart heart NOUN bracis-28402 143 5 , , PUNCT bracis-28402 143 6 banking banking NOUN bracis-28402 143 7 and and CCONJ bracis-28402 143 8 credit credit NOUN bracis-28402 143 9 , , PUNCT bracis-28402 143 10 even even ADV bracis-28402 143 11 for for ADP bracis-28402 143 12 a a DET bracis-28402 143 13 small small ADJ bracis-28402 143 14 number number NOUN bracis-28402 143 15 of of ADP bracis-28402 143 16 iterations iteration NOUN bracis-28402 143 17 , , PUNCT bracis-28402 143 18 or or CCONJ bracis-28402 143 19 25 25 NUM bracis-28402 143 20 or or CCONJ bracis-28402 143 21 100 100 NUM bracis-28402 143 22 , , PUNCT bracis-28402 143 23 the the DET bracis-28402 143 24 use use NOUN bracis-28402 143 25 of of ADP bracis-28402 143 26 no no DET bracis-28402 143 27 statistical statistical ADJ bracis-28402 143 28 test test NOUN bracis-28402 143 29 ( ( PUNCT bracis-28402 143 30 dummy dummy NOUN bracis-28402 143 31 ) ) PUNCT bracis-28402 143 32 has have AUX bracis-28402 143 33 led lead VERB bracis-28402 143 34 to to ADP bracis-28402 143 35 better well ADJ bracis-28402 143 36 average average ADJ bracis-28402 143 37 performances performance NOUN bracis-28402 143 38 of of ADP bracis-28402 143 39 algorithm algorithm NOUN bracis-28402 143 40     SPACE bracis-28402 143 41 1 1 NUM bracis-28402 143 42 . . PUNCT bracis-28402 144 1 among among ADP bracis-28402 144 2 the the DET bracis-28402 144 3 versions version NOUN bracis-28402 144 4 with with ADP bracis-28402 144 5 an an DET bracis-28402 144 6 actual actual ADJ bracis-28402 144 7 statistical statistical ADJ bracis-28402 144 8 test test NOUN bracis-28402 144 9 , , PUNCT bracis-28402 144 10 the the DET bracis-28402 144 11 paired pair VERB bracis-28402 144 12 t t NOUN bracis-28402 144 13 - - PUNCT bracis-28402 144 14 test test NOUN bracis-28402 144 15 with with ADP bracis-28402 144 16 relates relate VERB bracis-28402 144 17 samples sample NOUN bracis-28402 144 18 ( ( PUNCT bracis-28402 144 19 ttest_rel ttest_rel NOUN bracis-28402 144 20 ) ) PUNCT bracis-28402 144 21 has have AUX bracis-28402 144 22 led lead VERB bracis-28402 144 23 to to PART bracis-28402 144 24 better well ADV bracis-28402 144 25 or or CCONJ bracis-28402 144 26 almost almost ADV bracis-28402 144 27 equal equal ADJ bracis-28402 144 28 results result NOUN bracis-28402 144 29 on on ADP bracis-28402 144 30 average average ADJ bracis-28402 144 31 . . PUNCT bracis-28402 145 1 for for ADP bracis-28402 145 2 the the DET bracis-28402 145 3 spambase spambase NOUN bracis-28402 145 4 where where SCONJ bracis-28402 145 5 is be AUX bracis-28402 145 6 was be AUX bracis-28402 145 7 easy easy ADJ bracis-28402 145 8 to to PART bracis-28402 145 9 generate generate VERB bracis-28402 145 10 improved improved ADJ bracis-28402 145 11 models model NOUN bracis-28402 145 12 , , PUNCT bracis-28402 145 13 the the DET bracis-28402 145 14 difference difference NOUN bracis-28402 145 15 between between ADP bracis-28402 145 16 the the DET bracis-28402 145 17 dummy dummy NOUN bracis-28402 145 18 and and CCONJ bracis-28402 145 19 the the DET bracis-28402 145 20 other other ADJ bracis-28402 145 21 versions version NOUN bracis-28402 145 22 , , PUNCT bracis-28402 145 23 only only ADV bracis-28402 145 24 shows show NOUN bracis-28402 145 25 at at ADP bracis-28402 145 26 the the DET bracis-28402 145 27 limit limit NOUN bracis-28402 145 28 of of ADP bracis-28402 145 29 1000 1000 NUM bracis-28402 145 30 generations generation NOUN bracis-28402 145 31 . . PUNCT bracis-28402 146 1 overall overall ADV bracis-28402 146 2 , , PUNCT bracis-28402 146 3 these these DET bracis-28402 146 4 results result NOUN bracis-28402 146 5 suggest suggest VERB bracis-28402 146 6 that that SCONJ bracis-28402 146 7 in in ADP bracis-28402 146 8 a a DET bracis-28402 146 9 challenging challenging ADJ bracis-28402 146 10 scenario scenario NOUN bracis-28402 146 11 where where SCONJ bracis-28402 146 12 generating generate VERB bracis-28402 146 13 improved improved ADJ bracis-28402 146 14 models model NOUN bracis-28402 146 15 is be AUX bracis-28402 146 16 difficult difficult ADJ bracis-28402 146 17 , , PUNCT bracis-28402 146 18 the the DET bracis-28402 146 19 use use NOUN bracis-28402 146 20 of of ADP bracis-28402 146 21 statistical statistical ADJ bracis-28402 146 22 tests test NOUN bracis-28402 146 23 may may AUX bracis-28402 146 24 hinder hinder VERB bracis-28402 146 25 progress progress NOUN bracis-28402 146 26 by by ADP bracis-28402 146 27 imposing impose VERB bracis-28402 146 28 a a DET bracis-28402 146 29 an an DET bracis-28402 146 30 excessively excessively ADV bracis-28402 146 31 stringent stringent ADJ bracis-28402 146 32 standard standard NOUN bracis-28402 146 33 for for ADP bracis-28402 146 34 accepting accept VERB bracis-28402 146 35 new new ADJ bracis-28402 146 36 models model NOUN bracis-28402 146 37 . . PUNCT bracis-28402 147 1 fig fig NOUN bracis-28402 147 2 . . PUNCT bracis-28402 148 1 5 5 NUM bracis-28402 148 2 . . X bracis-28402 148 3 % % NOUN bracis-28402 148 4 of of ADP bracis-28402 148 5 improvement improvement NOUN bracis-28402 148 6 by by ADP bracis-28402 148 7 statistical statistical ADJ bracis-28402 148 8 test test NOUN bracis-28402 148 9 and and CCONJ bracis-28402 148 10 maximum maximum ADJ bracis-28402 148 11 number number NOUN bracis-28402 148 12 of of ADP bracis-28402 148 13 generations generation NOUN bracis-28402 148 14 for for ADP bracis-28402 148 15 each each DET bracis-28402 148 16 dataset dataset VERB bracis-28402 148 17 full full ADJ bracis-28402 148 18 size size NOUN bracis-28402 148 19 image image NOUN bracis-28402 148 20 6 6 NUM bracis-28402 148 21 conclusion conclusion NOUN bracis-28402 148 22 this this DET bracis-28402 148 23 study study NOUN bracis-28402 148 24 investigates investigate VERB bracis-28402 148 25 the the DET bracis-28402 148 26 effectiveness effectiveness NOUN bracis-28402 148 27 of of ADP bracis-28402 148 28 statistical statistical ADJ bracis-28402 148 29 tests test NOUN bracis-28402 148 30 commonly commonly ADV bracis-28402 148 31 used use VERB bracis-28402 148 32 for for ADP bracis-28402 148 33 selecting select VERB bracis-28402 148 34 the the DET bracis-28402 148 35 best good ADJ bracis-28402 148 36 machine machine NOUN bracis-28402 148 37 learning learning NOUN bracis-28402 148 38 ( ( PUNCT bracis-28402 148 39 ml ml NOUN bracis-28402 148 40 ) ) PUNCT bracis-28402 148 41 model model NOUN bracis-28402 148 42 when when SCONJ bracis-28402 148 43 applied apply VERB bracis-28402 148 44 over over ADP bracis-28402 148 45 larger large ADJ bracis-28402 148 46 periods period NOUN bracis-28402 148 47 of of ADP bracis-28402 148 48 time time NOUN bracis-28402 148 49 . . PUNCT bracis-28402 149 1 the the DET bracis-28402 149 2 study study NOUN bracis-28402 149 3 aims aim VERB bracis-28402 149 4 to to PART bracis-28402 149 5 understand understand VERB bracis-28402 149 6 whether whether SCONJ bracis-28402 149 7 a a DET bracis-28402 149 8 selection selection NOUN bracis-28402 149 9 procedure procedure NOUN bracis-28402 149 10 based base VERB bracis-28402 149 11 on on ADP bracis-28402 149 12 statistical statistical ADJ bracis-28402 149 13 tests test NOUN bracis-28402 149 14 leads lead VERB bracis-28402 149 15 to to ADP bracis-28402 149 16 higher high ADJ bracis-28402 149 17 quality quality NOUN bracis-28402 149 18 models model NOUN bracis-28402 149 19 after after ADP bracis-28402 149 20 a a DET bracis-28402 149 21 significant significant ADJ bracis-28402 149 22 number number NOUN bracis-28402 149 23 of of ADP bracis-28402 149 24 iterations iteration NOUN bracis-28402 149 25 . . PUNCT bracis-28402 150 1 additionally additionally ADV bracis-28402 150 2 , , PUNCT bracis-28402 150 3 the the DET bracis-28402 150 4 impact impact NOUN bracis-28402 150 5 of of ADP bracis-28402 150 6 the the DET bracis-28402 150 7 number number NOUN bracis-28402 150 8 of of ADP bracis-28402 150 9 tests test NOUN bracis-28402 150 10 ( ( PUNCT bracis-28402 150 11 number number NOUN bracis-28402 150 12 of of ADP bracis-28402 150 13 folds fold NOUN bracis-28402 150 14 in in ADP bracis-28402 150 15 cross cross ADJ bracis-28402 150 16 - - ADJ bracis-28402 150 17 validation validation NOUN bracis-28402 150 18 ) ) PUNCT bracis-28402 150 19 performed perform VERB bracis-28402 150 20 to to PART bracis-28402 150 21 acquire acquire VERB bracis-28402 150 22 data datum NOUN bracis-28402 150 23 for for ADP bracis-28402 150 24 these these DET bracis-28402 150 25 statistical statistical ADJ bracis-28402 150 26 tests test NOUN bracis-28402 150 27 and and CCONJ bracis-28402 150 28 the the DET bracis-28402 150 29 preferred preferred ADJ bracis-28402 150 30 statistical statistical ADJ bracis-28402 150 31 test test NOUN bracis-28402 150 32 for for ADP bracis-28402 150 33 different different ADJ bracis-28402 150 34 experimental experimental ADJ bracis-28402 150 35 time time NOUN bracis-28402 150 36 horizons horizon NOUN bracis-28402 150 37 are be AUX bracis-28402 150 38 examined examine VERB bracis-28402 150 39 . . PUNCT bracis-28402 151 1 in in ADP bracis-28402 151 2 summary summary NOUN bracis-28402 151 3 , , PUNCT bracis-28402 151 4 the the DET bracis-28402 151 5 analysis analysis NOUN bracis-28402 151 6 suggests suggest VERB bracis-28402 151 7 that that SCONJ bracis-28402 151 8 the the DET bracis-28402 151 9 use use NOUN bracis-28402 151 10 of of ADP bracis-28402 151 11 statistical statistical ADJ bracis-28402 151 12 tests test NOUN bracis-28402 151 13 in in ADP bracis-28402 151 14 ml ml NOUN bracis-28402 151 15 model model NOUN bracis-28402 151 16 selection selection NOUN bracis-28402 151 17 should should AUX bracis-28402 151 18 be be AUX bracis-28402 151 19 carefully carefully ADV bracis-28402 151 20 considered consider VERB bracis-28402 151 21 , , PUNCT bracis-28402 151 22 especially especially ADV bracis-28402 151 23 in in ADP bracis-28402 151 24 challenging challenging ADJ bracis-28402 151 25 scenarios scenario NOUN bracis-28402 151 26 , , PUNCT bracis-28402 151 27 as as SCONJ bracis-28402 151 28 they they PRON bracis-28402 151 29 may may AUX bracis-28402 151 30 hinder hinder VERB bracis-28402 151 31 progress progress NOUN bracis-28402 151 32 and and CCONJ bracis-28402 151 33 impose impose VERB bracis-28402 151 34 overly overly ADV bracis-28402 151 35 stringent stringent ADJ bracis-28402 151 36 criteria criterion NOUN bracis-28402 151 37 for for ADP bracis-28402 151 38 accepting accept VERB bracis-28402 151 39 new new ADJ bracis-28402 151 40 models model NOUN bracis-28402 151 41 . . PUNCT bracis-28402 152 1 although although SCONJ bracis-28402 152 2 the the DET bracis-28402 152 3 number number NOUN bracis-28402 152 4 of of ADP bracis-28402 152 5 datasets dataset NOUN bracis-28402 152 6 in in ADP bracis-28402 152 7 this this DET bracis-28402 152 8 study study NOUN bracis-28402 152 9 is be AUX bracis-28402 152 10 limited limit VERB bracis-28402 152 11 , , PUNCT bracis-28402 152 12 and and CCONJ bracis-28402 152 13 the the DET bracis-28402 152 14 proposed propose VERB bracis-28402 152 15 procedure procedure NOUN bracis-28402 152 16 did do AUX bracis-28402 152 17 not not PART bracis-28402 152 18 verify verify VERB bracis-28402 152 19 the the DET bracis-28402 152 20 assumptions assumption NOUN bracis-28402 152 21 of of ADP bracis-28402 152 22 the the DET bracis-28402 152 23 applied apply VERB bracis-28402 152 24 tests test NOUN bracis-28402 152 25 beforehand beforehand ADV bracis-28402 152 26 , , PUNCT bracis-28402 152 27 it it PRON bracis-28402 152 28 is be AUX bracis-28402 152 29 noteworthy noteworthy ADJ bracis-28402 152 30 that that SCONJ bracis-28402 152 31 the the DET bracis-28402 152 32 dominance dominance NOUN bracis-28402 152 33 of of ADP bracis-28402 152 34 the the DET bracis-28402 152 35 versions version NOUN bracis-28402 152 36 without without ADP bracis-28402 152 37 statistical statistical ADJ bracis-28402 152 38 tests test NOUN bracis-28402 152 39 remained remain VERB bracis-28402 152 40 consistent consistent ADJ bracis-28402 152 41 . . PUNCT bracis-28402 153 1 this this PRON bracis-28402 153 2 highlights highlight VERB bracis-28402 153 3 the the DET bracis-28402 153 4 importance importance NOUN bracis-28402 153 5 of of ADP bracis-28402 153 6 conducting conduct VERB bracis-28402 153 7 further further ADJ bracis-28402 153 8 research research NOUN bracis-28402 153 9 and and CCONJ bracis-28402 153 10 exploration exploration NOUN bracis-28402 153 11 in in ADP bracis-28402 153 12 this this DET bracis-28402 153 13 area area NOUN bracis-28402 153 14 . . PUNCT bracis-28402 154 1 the the DET bracis-28402 154 2 use use NOUN bracis-28402 154 3 of of ADP bracis-28402 154 4 statistical statistical ADJ bracis-28402 154 5 tests test NOUN bracis-28402 154 6 of of ADP bracis-28402 154 7 hypothesis hypothesis NOUN bracis-28402 154 8 is be AUX bracis-28402 154 9 fundamental fundamental ADJ bracis-28402 154 10 in in ADP bracis-28402 154 11 many many ADJ bracis-28402 154 12 scientific scientific ADJ bracis-28402 154 13 fields field NOUN bracis-28402 154 14 , , PUNCT bracis-28402 154 15 and and CCONJ bracis-28402 154 16 it it PRON bracis-28402 154 17 is be AUX bracis-28402 154 18 crucial crucial ADJ bracis-28402 154 19 to to PART bracis-28402 154 20 better well ADV bracis-28402 154 21 understand understand VERB bracis-28402 154 22 their their PRON bracis-28402 154 23 impact impact NOUN bracis-28402 154 24 on on ADP bracis-28402 154 25 the the DET bracis-28402 154 26 selection selection NOUN bracis-28402 154 27 of of ADP bracis-28402 154 28 machine machine NOUN bracis-28402 154 29 learning learning NOUN bracis-28402 154 30 models model NOUN bracis-28402 154 31 . . PUNCT bracis-28402 155 1 references reference NOUN bracis-28402 155 2 aygun aygun PROPN bracis-28402 155 3 , , PUNCT bracis-28402 155 4 b. b. PROPN bracis-28402 155 5 , , PUNCT bracis-28402 155 6 gunay gunay PROPN bracis-28402 155 7 , , PUNCT bracis-28402 155 8 e.k e.k PROPN bracis-28402 155 9 . . PROPN bracis-28402 155 10 : : PUNCT bracis-28402 156 1 comparison comparison NOUN bracis-28402 156 2 of of ADP bracis-28402 156 3 statistical statistical ADJ bracis-28402 156 4 and and CCONJ bracis-28402 156 5 machine machine NOUN bracis-28402 156 6 learning learn VERB bracis-28402 156 7 algorithms algorithm NOUN bracis-28402 156 8 for for ADP bracis-28402 156 9 forecasting forecast VERB bracis-28402 156 10 daily daily ADJ bracis-28402 156 11 bitcoin bitcoin ADJ bracis-28402 156 12 returns return NOUN bracis-28402 156 13 . . PUNCT bracis-28402 157 1 avrupa avrupa PROPN bracis-28402 157 2 bilim bilim PROPN bracis-28402 157 3 ve ve AUX bracis-28402 157 4 teknoloji teknoloji PROPN bracis-28402 157 5 dergisi dergisi ADJ bracis-28402 157 6 ( ( PUNCT bracis-28402 157 7 21 21 NUM bracis-28402 157 8 ) ) PUNCT bracis-28402 157 9 , , PUNCT bracis-28402 157 10 pp pp ADP bracis-28402 157 11 . . PUNCT bracis-28402 158 1 444–454 444–454 NUM bracis-28402 158 2 ( ( PUNCT bracis-28402 158 3 2021 2021 NUM bracis-28402 158 4 ) ) PUNCT bracis-28402 158 5 google google PROPN bracis-28402 158 6 scholar scholar NOUN bracis-28402 158 7     SPACE bracis-28402 158 8 bao bao PROPN bracis-28402 158 9 , , PUNCT bracis-28402 158 10 d. d. PROPN bracis-28402 158 11 , , PUNCT bracis-28402 158 12 et et PROPN bracis-28402 158 13 al al PROPN bracis-28402 158 14 . . PROPN bracis-28402 158 15 : : PUNCT bracis-28402 159 1 discriminating discriminate VERB bracis-28402 159 2 between between ADP bracis-28402 159 3 p16 p16 NOUN bracis-28402 159 4 - - PUNCT bracis-28402 159 5 negative negative ADJ bracis-28402 159 6 oropharyngeal oropharyngeal NOUN bracis-28402 159 7 and and CCONJ bracis-28402 159 8 non non ADJ bracis-28402 159 9 - - ADJ bracis-28402 159 10 oropharyngeal oropharyngeal ADJ bracis-28402 159 11 origins origin NOUN bracis-28402 159 12 by by ADP bracis-28402 159 13 their their PRON bracis-28402 159 14 metastatic metastatic ADJ bracis-28402 159 15 lymph lymph NOUN bracis-28402 159 16 nodes node NOUN bracis-28402 159 17 using use VERB bracis-28402 159 18 machine machine NOUN bracis-28402 159 19 learning learn VERB bracis-28402 159 20 approach approach NOUN bracis-28402 159 21 based base VERB bracis-28402 159 22 on on ADP bracis-28402 159 23 mri mri NOUN bracis-28402 159 24 radiomics radiomic NOUN bracis-28402 159 25 ( ( PUNCT bracis-28402 159 26 2022 2022 NUM bracis-28402 159 27 ) ) PUNCT bracis-28402 159 28 google google PROPN bracis-28402 159 29 scholar scholar NOUN bracis-28402 159 30     SPACE bracis-28402 159 31 benavoli benavoli NOUN bracis-28402 159 32 , , PUNCT bracis-28402 159 33 a. a. NOUN bracis-28402 159 34 , , PUNCT bracis-28402 159 35 corani corani PROPN bracis-28402 159 36 , , PUNCT bracis-28402 159 37 g. g. PROPN bracis-28402 159 38 , , PUNCT bracis-28402 159 39 demšar demšar PROPN bracis-28402 159 40 , , PUNCT bracis-28402 159 41 j. j. PROPN bracis-28402 159 42 , , PUNCT bracis-28402 159 43 zaffalon zaffalon PROPN bracis-28402 159 44 , , PUNCT bracis-28402 159 45 m. m. NOUN bracis-28402 159 46 : : PUNCT bracis-28402 159 47 time time NOUN bracis-28402 159 48 for for ADP bracis-28402 159 49 a a DET bracis-28402 159 50 change change NOUN bracis-28402 159 51 : : PUNCT bracis-28402 159 52 a a DET bracis-28402 159 53 tutorial tutorial NOUN bracis-28402 159 54 for for ADP bracis-28402 159 55 comparing compare VERB bracis-28402 159 56 multiple multiple ADJ bracis-28402 159 57 classifiers classifier NOUN bracis-28402 159 58 through through ADP bracis-28402 159 59 bayesian bayesian NOUN bracis-28402 159 60 analysis analysis NOUN bracis-28402 159 61 . . PUNCT bracis-28402 160 1 j. j. PROPN bracis-28402 160 2 mach mach PROPN bracis-28402 160 3 . . PUNCT bracis-28402 161 1 learn learn VERB bracis-28402 161 2 . . PUNCT bracis-28402 162 1 res re NOUN bracis-28402 162 2 . . PUNCT bracis-28402 163 1 18(77 18(77 NUM bracis-28402 163 2 ) ) PUNCT bracis-28402 163 3 , , PUNCT bracis-28402 163 4 1–36 1–36 PROPN bracis-28402 163 5 ( ( PUNCT bracis-28402 163 6 2017 2017 NUM bracis-28402 163 7 ) ) PUNCT bracis-28402 163 8 . . PUNCT bracis-28402 164 1 http://jmlr.org/papers/v18/16-305.html http://jmlr.org/papers/v18/16-305.html PROPN bracis-28402 165 1 bender bender PROPN bracis-28402 165 2 , , PUNCT bracis-28402 165 3 a. a. PROPN bracis-28402 165 4 , , PUNCT bracis-28402 165 5 schneider schneider PROPN bracis-28402 165 6 , , PUNCT bracis-28402 165 7 n. n. NOUN bracis-28402 165 8 , , PUNCT bracis-28402 165 9 segler segler NOUN bracis-28402 165 10 , , PUNCT bracis-28402 165 11 m. m. NOUN bracis-28402 165 12 , , PUNCT bracis-28402 165 13 patrick patrick PROPN bracis-28402 165 14 walters walters PROPN bracis-28402 165 15 , , PUNCT bracis-28402 165 16 w. w. PROPN bracis-28402 165 17 , , PUNCT bracis-28402 165 18 engkvist engkvist NOUN bracis-28402 165 19 , , PUNCT bracis-28402 165 20 o. o. PROPN bracis-28402 165 21 , , PUNCT bracis-28402 165 22 rodrigues rodrigues PROPN bracis-28402 165 23 , , PUNCT bracis-28402 165 24 t. t. NOUN bracis-28402 165 25 : : PUNCT bracis-28402 165 26 evaluation evaluation NOUN bracis-28402 165 27 guidelines guideline NOUN bracis-28402 165 28 for for ADP bracis-28402 165 29 machine machine NOUN bracis-28402 165 30 learning learning NOUN bracis-28402 165 31 tools tool NOUN bracis-28402 165 32 in in ADP bracis-28402 165 33 the the DET bracis-28402 165 34 chemical chemical NOUN bracis-28402 165 35 sciences science NOUN bracis-28402 165 36 . . PUNCT bracis-28402 166 1 nat nat PROPN bracis-28402 166 2 . . PUNCT bracis-28402 167 1 rev rev PROPN bracis-28402 167 2 . . PROPN bracis-28402 167 3 chem chem PROPN bracis-28402 167 4 . . PUNCT bracis-28402 168 1 6(6 6(6 NUM bracis-28402 168 2 ) ) PUNCT bracis-28402 168 3 , , PUNCT bracis-28402 168 4 428–442 428–442 NUM bracis-28402 168 5 ( ( PUNCT bracis-28402 168 6 2022 2022 NUM bracis-28402 168 7 ) ) PUNCT bracis-28402 168 8 article article NOUN bracis-28402 168 9     SPACE bracis-28402 168 10 google google PROPN bracis-28402 168 11 scholar scholar NOUN bracis-28402 168 12     SPACE bracis-28402 168 13 corani corani PROPN bracis-28402 168 14 , , PUNCT bracis-28402 168 15 g. g. PROPN bracis-28402 168 16 , , PUNCT bracis-28402 168 17 benavoli benavoli NOUN bracis-28402 168 18 , , PUNCT bracis-28402 168 19 a. a. NOUN bracis-28402 168 20 : : PUNCT bracis-28402 168 21 a a DET bracis-28402 168 22 bayesian bayesian NOUN bracis-28402 168 23 approach approach NOUN bracis-28402 168 24 for for ADP bracis-28402 168 25 comparing compare VERB bracis-28402 168 26 cross cross ADJ bracis-28402 168 27 - - ADJ bracis-28402 168 28 validated validated ADJ bracis-28402 168 29 algorithms algorithm NOUN bracis-28402 168 30 on on ADP bracis-28402 168 31 multiple multiple ADJ bracis-28402 168 32 data datum NOUN bracis-28402 168 33 sets set NOUN bracis-28402 168 34 . . PUNCT bracis-28402 169 1 mach mach NOUN bracis-28402 169 2 . . PUNCT bracis-28402 170 1 learn learn VERB bracis-28402 170 2 . . PUNCT bracis-28402 171 1 100(2–3 100(2–3 NUM bracis-28402 171 2 ) ) PUNCT bracis-28402 171 3 , , PUNCT bracis-28402 171 4 285–304 285–304 NUM bracis-28402 171 5 ( ( PUNCT bracis-28402 171 6 2015 2015 NUM bracis-28402 171 7 ) ) PUNCT bracis-28402 171 8 article article NOUN bracis-28402 171 9     SPACE bracis-28402 171 10 mathscinet mathscinet NOUN bracis-28402 171 11     SPACE bracis-28402 171 12 math math NOUN bracis-28402 171 13     SPACE bracis-28402 171 14 google google PROPN bracis-28402 171 15 scholar scholar NOUN bracis-28402 171 16     SPACE bracis-28402 171 17 dua dua PROPN bracis-28402 171 18 , , PUNCT bracis-28402 171 19 d. d. PROPN bracis-28402 171 20 , , PUNCT bracis-28402 171 21 graff graff PROPN bracis-28402 171 22 , , PUNCT bracis-28402 171 23 c. c. PROPN bracis-28402 171 24 : : PUNCT bracis-28402 171 25 uci uci PROPN bracis-28402 171 26 machine machine NOUN bracis-28402 171 27 learning learn VERB bracis-28402 171 28 repository repository NOUN bracis-28402 171 29 ( ( PUNCT bracis-28402 171 30 2017 2017 NUM bracis-28402 171 31 ) ) PUNCT bracis-28402 171 32 . . PUNCT bracis-28402 172 1 http://archive.ics.uci.edu/ml http://archive.ics.uci.edu/ml NUM bracis-28402 172 2 fagerland fagerland NOUN bracis-28402 172 3 , , PUNCT bracis-28402 172 4 m.w m.w PROPN bracis-28402 172 5 . . PROPN bracis-28402 172 6 : : PUNCT bracis-28402 172 7 t t NOUN bracis-28402 172 8 - - PUNCT bracis-28402 172 9 tests test NOUN bracis-28402 172 10 , , PUNCT bracis-28402 172 11 non non ADJ bracis-28402 172 12 - - ADJ bracis-28402 172 13 parametric parametric ADJ bracis-28402 172 14 tests test NOUN bracis-28402 172 15 , , PUNCT bracis-28402 172 16 and and CCONJ bracis-28402 172 17 large large ADJ bracis-28402 172 18 studies study NOUN bracis-28402 172 19 - - PUNCT bracis-28402 172 20 a a DET bracis-28402 172 21 paradox paradox NOUN bracis-28402 172 22 of of ADP bracis-28402 172 23 statistical statistical ADJ bracis-28402 172 24 practice practice NOUN bracis-28402 172 25 ? ? PUNCT bracis-28402 173 1 bmc bmc PROPN bracis-28402 173 2 med med PROPN bracis-28402 173 3 . . PUNCT bracis-28402 174 1 res re NOUN bracis-28402 174 2 . . PUNCT bracis-28402 175 1 methodol methodol PROPN bracis-28402 175 2 . . PUNCT bracis-28402 176 1 12(1 12(1 NUM bracis-28402 176 2 ) ) PUNCT bracis-28402 176 3 , , PUNCT bracis-28402 176 4 1–7 1–7 NUM bracis-28402 176 5 ( ( PUNCT bracis-28402 176 6 2012 2012 NUM bracis-28402 176 7 ) ) PUNCT bracis-28402 176 8 article article NOUN bracis-28402 176 9     SPACE bracis-28402 176 10 google google PROPN bracis-28402 176 11 scholar scholar NOUN bracis-28402 176 12     SPACE bracis-28402 176 13 hair hair NOUN bracis-28402 176 14 , , PUNCT bracis-28402 176 15 j.f j.f PROPN bracis-28402 176 16 . . PROPN bracis-28402 176 17 , , PUNCT bracis-28402 176 18 jr jr PROPN bracis-28402 176 19 . . PROPN bracis-28402 176 20 , , PUNCT bracis-28402 176 21 sarstedt sarstedt NOUN bracis-28402 176 22 , , PUNCT bracis-28402 176 23 m. m. NOUN bracis-28402 176 24 : : PUNCT bracis-28402 176 25 data data PROPN bracis-28402 176 26 , , PUNCT bracis-28402 176 27 measurement measurement NOUN bracis-28402 176 28 , , PUNCT bracis-28402 176 29 and and CCONJ bracis-28402 176 30 causal causal ADJ bracis-28402 176 31 inferences inference NOUN bracis-28402 176 32 in in ADP bracis-28402 176 33 machine machine NOUN bracis-28402 176 34 learning learning NOUN bracis-28402 176 35 : : PUNCT bracis-28402 176 36 opportunities opportunity NOUN bracis-28402 176 37 and and CCONJ bracis-28402 176 38 challenges challenge NOUN bracis-28402 176 39 for for ADP bracis-28402 176 40 marketing marketing NOUN bracis-28402 176 41 . . PUNCT bracis-28402 177 1 j. j. PROPN bracis-28402 177 2 market market PROPN bracis-28402 177 3 . . PUNCT bracis-28402 178 1 theory theory NOUN bracis-28402 178 2 practice practice NOUN bracis-28402 178 3 29(1 29(1 NUM bracis-28402 178 4 ) ) PUNCT bracis-28402 178 5 , , PUNCT bracis-28402 178 6 65–77 65–77 NUM bracis-28402 178 7 ( ( PUNCT bracis-28402 178 8 2021 2021 NUM bracis-28402 178 9 ) ) PUNCT bracis-28402 178 10 article article NOUN bracis-28402 178 11     SPACE bracis-28402 178 12 google google PROPN bracis-28402 178 13 scholar scholar NOUN bracis-28402 178 14     SPACE bracis-28402 178 15 hopkins hopkin NOUN bracis-28402 178 16 , , PUNCT bracis-28402 178 17 m. m. NOUN bracis-28402 178 18 , , PUNCT bracis-28402 178 19 reeber reeber PROPN bracis-28402 178 20 , , PUNCT bracis-28402 178 21 e. e. PROPN bracis-28402 178 22 , , PUNCT bracis-28402 178 23 forman forman PROPN bracis-28402 178 24 , , PUNCT bracis-28402 178 25 g. g. PROPN bracis-28402 178 26 , , PUNCT bracis-28402 178 27 suermondt suermondt PROPN bracis-28402 178 28 , , PUNCT bracis-28402 178 29 j. j. PROPN bracis-28402 178 30 : : PUNCT bracis-28402 178 31 spambase spambase PROPN bracis-28402 178 32 . . PUNCT bracis-28402 179 1 uci uci PROPN bracis-28402 179 2 machine machine NOUN bracis-28402 179 3 learning learn VERB bracis-28402 179 4 repository repository NOUN bracis-28402 179 5 ( ( PUNCT bracis-28402 179 6 1999 1999 NUM bracis-28402 179 7 ) ) PUNCT bracis-28402 179 8 . . PUNCT bracis-28402 180 1 https://doi.org/10.24432/c53g6x https://doi.org/10.24432/c53g6x PROPN bracis-28402 180 2 article article NOUN bracis-28402 180 3     SPACE bracis-28402 180 4 google google PROPN bracis-28402 180 5 scholar scholar NOUN bracis-28402 180 6     SPACE bracis-28402 180 7 janosi janosi NOUN bracis-28402 180 8 , , PUNCT bracis-28402 180 9 a. a. NOUN bracis-28402 180 10 , , PUNCT bracis-28402 180 11 steinbrunn steinbrunn NOUN bracis-28402 180 12 , , PUNCT bracis-28402 180 13 w. w. PROPN bracis-28402 180 14 , , PUNCT bracis-28402 180 15 pfisterer pfisterer NOUN bracis-28402 180 16 , , PUNCT bracis-28402 180 17 m. m. NOUN bracis-28402 180 18 , , PUNCT bracis-28402 180 19 detrano detrano PROPN bracis-28402 180 20 , , PUNCT bracis-28402 180 21 r. r. PROPN bracis-28402 180 22 , , PUNCT bracis-28402 180 23 m.d m.d PROPN bracis-28402 180 24 . . PROPN bracis-28402 180 25 , , PUNCT bracis-28402 180 26 m. m. NOUN bracis-28402 180 27 : : PUNCT bracis-28402 180 28 heart heart NOUN bracis-28402 180 29 disease disease NOUN bracis-28402 180 30 . . PUNCT bracis-28402 181 1 uci uci PROPN bracis-28402 181 2 machine machine NOUN bracis-28402 181 3 learning learn VERB bracis-28402 181 4 repository repository NOUN bracis-28402 181 5 ( ( PUNCT bracis-28402 181 6 1988 1988 NUM bracis-28402 181 7 ) ) PUNCT bracis-28402 181 8 . . PUNCT bracis-28402 182 1 https://doi.org/10.24432/c52p4x https://doi.org/10.24432/c52p4x PROPN bracis-28402 182 2 kim kim PROPN bracis-28402 182 3 , , PUNCT bracis-28402 182 4 t.k t.k PROPN bracis-28402 182 5 . . PROPN bracis-28402 182 6 : : PUNCT bracis-28402 183 1 t t PROPN bracis-28402 183 2 test test NOUN bracis-28402 183 3 as as ADP bracis-28402 183 4 a a DET bracis-28402 183 5 parametric parametric ADJ bracis-28402 183 6 statistic statistic NOUN bracis-28402 183 7 . . PUNCT bracis-28402 184 1 korean korean ADJ bracis-28402 184 2 j. j. PROPN bracis-28402 184 3 anesthesiol anesthesiol PROPN bracis-28402 184 4 . . PUNCT bracis-28402 185 1 68(6 68(6 NOUN bracis-28402 185 2 ) ) PUNCT bracis-28402 185 3 , , PUNCT bracis-28402 185 4 540–546 540–546 NUM bracis-28402 185 5 ( ( PUNCT bracis-28402 185 6 2015 2015 NUM bracis-28402 185 7 ) ) PUNCT bracis-28402 185 8 article article NOUN bracis-28402 185 9     SPACE bracis-28402 185 10 mathscinet mathscinet NOUN bracis-28402 185 11     SPACE bracis-28402 185 12 google google PROPN bracis-28402 185 13 scholar scholar NOUN bracis-28402 185 14     SPACE bracis-28402 185 15 morettin morettin NOUN bracis-28402 185 16 , , PUNCT bracis-28402 185 17 p.a p.a PROPN bracis-28402 185 18 . . PROPN bracis-28402 185 19 , , PUNCT bracis-28402 185 20 bussab bussab PROPN bracis-28402 185 21 , , PUNCT bracis-28402 185 22 w.o w.o PROPN bracis-28402 185 23 . . PROPN bracis-28402 185 24 : : PUNCT bracis-28402 185 25 estatística estatística PROPN bracis-28402 185 26 básica básica PROPN bracis-28402 185 27 . . PUNCT bracis-28402 186 1 saraiva saraiva PROPN bracis-28402 186 2 educação educação PROPN bracis-28402 186 3 sa sa PROPN bracis-28402 186 4 ( ( PUNCT bracis-28402 186 5 2017 2017 NUM bracis-28402 186 6 ) ) PUNCT bracis-28402 186 7 google google PROPN bracis-28402 186 8 scholar scholar NOUN bracis-28402 186 9     SPACE bracis-28402 186 10 moro moro PROPN bracis-28402 186 11 , , PUNCT bracis-28402 186 12 s. s. PROPN bracis-28402 186 13 , , PUNCT bracis-28402 186 14 rita rita PROPN bracis-28402 186 15 , , PUNCT bracis-28402 186 16 p. p. PROPN bracis-28402 186 17 , , PUNCT bracis-28402 186 18 cortez cortez PROPN bracis-28402 186 19 , , PUNCT bracis-28402 186 20 p. p. NOUN bracis-28402 186 21 : : PUNCT bracis-28402 186 22 bank bank NOUN bracis-28402 186 23 marketing marketing NOUN bracis-28402 186 24 . . PUNCT bracis-28402 187 1 uci uci PROPN bracis-28402 187 2 machine machine NOUN bracis-28402 187 3 learning learn VERB bracis-28402 187 4 repository repository NOUN bracis-28402 187 5 ( ( PUNCT bracis-28402 187 6 2012 2012 NUM bracis-28402 187 7 ) ) PUNCT bracis-28402 187 8 . . PUNCT bracis-28402 188 1 https://doi.org/10.24432/c5k306 https://doi.org/10.24432/c5k306 PROPN bracis-28402 188 2 article article NOUN bracis-28402 188 3     SPACE bracis-28402 188 4 google google PROPN bracis-28402 188 5 scholar scholar NOUN bracis-28402 188 6     SPACE bracis-28402 188 7 trawiński trawiński PROPN bracis-28402 188 8 , , PUNCT bracis-28402 188 9 b. b. PROPN bracis-28402 188 10 , , PUNCT bracis-28402 188 11 smetek smetek NOUN bracis-28402 188 12 , , PUNCT bracis-28402 188 13 m. m. NOUN bracis-28402 188 14 , , PUNCT bracis-28402 188 15 telec telec INTJ bracis-28402 188 16 , , PUNCT bracis-28402 188 17 z. z. PROPN bracis-28402 188 18 , , PUNCT bracis-28402 188 19 lasota lasota PROPN bracis-28402 188 20 , , PUNCT bracis-28402 188 21 t. t. PROPN bracis-28402 188 22 : : PUNCT bracis-28402 188 23 nonparametric nonparametric ADJ bracis-28402 188 24 statistical statistical ADJ bracis-28402 188 25 analysis analysis NOUN bracis-28402 188 26 for for ADP bracis-28402 188 27 multiple multiple ADJ bracis-28402 188 28 comparison comparison NOUN bracis-28402 188 29 of of ADP bracis-28402 188 30 machine machine NOUN bracis-28402 188 31 learning learn VERB bracis-28402 188 32 regression regression NOUN bracis-28402 188 33 algorithms algorithm NOUN bracis-28402 188 34 . . PUNCT bracis-28402 189 1 int int NOUN bracis-28402 189 2 . . PUNCT bracis-28402 190 1 j. j. PROPN bracis-28402 190 2 appl appl PROPN bracis-28402 190 3 . . PROPN bracis-28402 190 4 math math PROPN bracis-28402 190 5 . . PUNCT bracis-28402 191 1 comput comput NOUN bracis-28402 191 2 . . PUNCT bracis-28402 192 1 sci sci PROPN bracis-28402 192 2 . . PUNCT bracis-28402 192 3 22(4 22(4 NUM bracis-28402 192 4 ) ) PUNCT bracis-28402 192 5 , , PUNCT bracis-28402 192 6 867–881 867–881 NUM bracis-28402 192 7 ( ( PUNCT bracis-28402 192 8 2012 2012 NUM bracis-28402 192 9 ) ) PUNCT bracis-28402 192 10 article article NOUN bracis-28402 192 11     SPACE bracis-28402 192 12 mathscinet mathscinet NOUN bracis-28402 192 13     SPACE bracis-28402 192 14 math math NOUN bracis-28402 192 15     SPACE bracis-28402 192 16 google google PROPN bracis-28402 192 17 scholar scholar NOUN bracis-28402 192 18     SPACE bracis-28402 192 19 van van PROPN bracis-28402 192 20 rijsbergen rijsbergen PROPN bracis-28402 192 21 , , PUNCT bracis-28402 192 22 c.j c.j PROPN bracis-28402 192 23 . . PROPN bracis-28402 192 24 : : PUNCT bracis-28402 192 25 information information NOUN bracis-28402 192 26 retrieval retrieval NOUN bracis-28402 192 27 . . PUNCT bracis-28402 193 1 ( ( PUNCT bracis-28402 193 2 no no DET bracis-28402 193 3 title title NOUN bracis-28402 193 4 ) ) PUNCT bracis-28402 193 5 ( ( PUNCT bracis-28402 193 6 1979 1979 NUM bracis-28402 193 7 ) ) PUNCT bracis-28402 193 8 google google PROPN bracis-28402 193 9 scholar scholar NOUN bracis-28402 193 10     SPACE bracis-28402 193 11 virtanen virtanen NOUN bracis-28402 193 12 , , PUNCT bracis-28402 193 13 p. p. PROPN bracis-28402 193 14 , , PUNCT bracis-28402 193 15 et et PROPN bracis-28402 193 16 al al PROPN bracis-28402 193 17 . . PUNCT bracis-28402 193 18 : : PUNCT bracis-28402 194 1 scipy scipy X bracis-28402 194 2 1.0 1.0 NUM bracis-28402 194 3 contributors contributor NOUN bracis-28402 194 4 : : PUNCT bracis-28402 194 5 scipy scipy PROPN bracis-28402 194 6 1.0 1.0 NUM bracis-28402 194 7 : : PUNCT bracis-28402 194 8 fundamental fundamental ADJ bracis-28402 194 9 algorithms algorithm NOUN bracis-28402 194 10 for for ADP bracis-28402 194 11 scientific scientific ADJ bracis-28402 194 12 computing computing NOUN bracis-28402 194 13 in in ADP bracis-28402 194 14 python python PROPN bracis-28402 194 15 . . PUNCT bracis-28402 195 1 nature nature NOUN bracis-28402 195 2 methods method NOUN bracis-28402 195 3 17 17 NUM bracis-28402 195 4 , , PUNCT bracis-28402 195 5 261–272 261–272 NUM bracis-28402 195 6 ( ( PUNCT bracis-28402 195 7 2020 2020 NUM bracis-28402 195 8 ) ) PUNCT bracis-28402 195 9 . . PUNCT bracis-28402 196 1 https://doi.org/10.1038/s41592-019-0686-2 https://doi.org/10.1038/s41592-019-0686-2 PROPN bracis-28402 196 2 wong wong PROPN bracis-28402 196 3 , , PUNCT bracis-28402 196 4 t.t t.t PROPN bracis-28402 196 5 . . PROPN bracis-28402 196 6 , , PUNCT bracis-28402 196 7 yeh yeh PROPN bracis-28402 196 8 , , PUNCT bracis-28402 196 9 p.y p.y PROPN bracis-28402 196 10 . . PROPN bracis-28402 196 11 : : PUNCT bracis-28402 197 1 reliable reliable ADJ bracis-28402 197 2 accuracy accuracy NOUN bracis-28402 197 3 estimates estimate NOUN bracis-28402 197 4 from from ADP bracis-28402 197 5 k k ADJ bracis-28402 197 6 - - ADJ bracis-28402 197 7 fold fold ADJ bracis-28402 197 8 cross cross NOUN bracis-28402 197 9 validation validation NOUN bracis-28402 197 10 . . PUNCT bracis-28402 198 1 ieee ieee PROPN bracis-28402 198 2 trans trans PROPN bracis-28402 198 3 . . PROPN bracis-28402 199 1 knowl knowl PROPN bracis-28402 199 2 . . PUNCT bracis-28402 200 1 data data PROPN bracis-28402 200 2 eng eng PROPN bracis-28402 200 3 . . PUNCT bracis-28402 201 1 32(8 32(8 NUM bracis-28402 201 2 ) ) PUNCT bracis-28402 201 3 , , PUNCT bracis-28402 202 1 1586–1594 1586–1594 NUM bracis-28402 202 2 ( ( PUNCT bracis-28402 202 3 2019 2019 NUM bracis-28402 202 4 ) ) PUNCT bracis-28402 202 5 article article NOUN bracis-28402 202 6     SPACE bracis-28402 202 7 google google PROPN bracis-28402 202 8 scholar scholar NOUN bracis-28402 202 9     SPACE bracis-28402 202 10 yeh yeh PROPN bracis-28402 202 11 , , PUNCT bracis-28402 202 12 i.c i.c PROPN bracis-28402 202 13 . . PROPN bracis-28402 202 14 : : PUNCT bracis-28402 203 1 default default NOUN bracis-28402 203 2 of of ADP bracis-28402 203 3 credit credit NOUN bracis-28402 203 4 card card NOUN bracis-28402 203 5 clients client NOUN bracis-28402 203 6 . . PUNCT bracis-28402 204 1 uci uci PROPN bracis-28402 204 2 mach mach PROPN bracis-28402 204 3 . . PUNCT bracis-28402 205 1 learn learn VERB bracis-28402 205 2 . . PUNCT bracis-28402 206 1 repository repository NOUN bracis-28402 206 2 ( ( PUNCT bracis-28402 206 3 2016 2016 NUM bracis-28402 206 4 ) ) PUNCT bracis-28402 206 5 . . PUNCT bracis-28402 207 1 https://doi.org/10.24432/c55s3h https://doi.org/10.24432/c55s3h PROPN bracis-28402 207 2 article article NOUN bracis-28402 207 3     SPACE bracis-28402 207 4 google google PROPN bracis-28402 207 5 scholar scholar NOUN bracis-28402 207 6     SPACE bracis-28402 207 7 download download NOUN bracis-28402 207 8 references reference NOUN bracis-28402 207 9 acknowledgments acknowledgment NOUN bracis-28402 207 10 this this DET bracis-28402 207 11 work work NOUN bracis-28402 207 12 was be AUX bracis-28402 207 13 supported support VERB bracis-28402 207 14 by by ADP bracis-28402 207 15 cnpq cnpq PROPN bracis-28402 207 16 national national PROPN bracis-28402 207 17 council council PROPN bracis-28402 207 18 for for ADP bracis-28402 207 19 scientific scientific ADJ bracis-28402 207 20 and and CCONJ bracis-28402 207 21 technological technological ADJ bracis-28402 207 22 development development NOUN bracis-28402 207 23 , , PUNCT bracis-28402 207 24 capes cape NOUN bracis-28402 207 25 coordination coordination NOUN bracis-28402 207 26 for for ADP bracis-28402 207 27 the the DET bracis-28402 207 28 improvement improvement NOUN bracis-28402 207 29 of of ADP bracis-28402 207 30 higher high ADJ bracis-28402 207 31 education education NOUN bracis-28402 207 32 personnel personnel NOUN bracis-28402 207 33 and and CCONJ bracis-28402 207 34 ufop ufop ADJ bracis-28402 207 35 federal federal PROPN bracis-28402 207 36 university university PROPN bracis-28402 207 37 of of ADP bracis-28402 207 38 ouro ouro PROPN bracis-28402 207 39 preto preto PROPN bracis-28402 207 40 . . PUNCT bracis-28402 208 1 author author NOUN bracis-28402 208 2 information information NOUN bracis-28402 208 3 authors author NOUN bracis-28402 208 4 and and CCONJ bracis-28402 208 5 affiliations affiliation NOUN bracis-28402 208 6 graduate graduate NOUN bracis-28402 208 7 program program NOUN bracis-28402 208 8 on on ADP bracis-28402 208 9 computer computer NOUN bracis-28402 208 10 science science NOUN bracis-28402 208 11 , , PUNCT bracis-28402 208 12 universidade universidade PROPN bracis-28402 208 13 federal federal PROPN bracis-28402 208 14 de de PROPN bracis-28402 208 15 ouro ouro PROPN bracis-28402 208 16 preto preto PROPN bracis-28402 208 17 , , PUNCT bracis-28402 208 18 ouro ouro PROPN bracis-28402 208 19 preto preto PROPN bracis-28402 208 20 , , PUNCT bracis-28402 208 21 brazil brazil PROPN bracis-28402 208 22 marcel marcel PROPN bracis-28402 208 23 chacon chacon PROPN bracis-28402 208 24 gonçalves gonçalves PROPN bracis-28402 208 25 department department PROPN bracis-28402 208 26 of of ADP bracis-28402 208 27 computer computer NOUN bracis-28402 208 28 science science NOUN bracis-28402 208 29 , , PUNCT bracis-28402 208 30 universidade universidade PROPN bracis-28402 208 31 federal federal PROPN bracis-28402 208 32 de de PROPN bracis-28402 208 33 ouro ouro PROPN bracis-28402 208 34 preto preto PROPN bracis-28402 208 35 , , PUNCT bracis-28402 208 36 ouro ouro PROPN bracis-28402 208 37 preto preto PROPN bracis-28402 208 38 , , PUNCT bracis-28402 208 39 brazil brazil PROPN bracis-28402 208 40 rodrigo rodrigo PROPN bracis-28402 208 41 silva silva PROPN bracis-28402 208 42 authors authors PROPN bracis-28402 208 43 marcel marcel PROPN bracis-28402 208 44 chacon chacon PROPN bracis-28402 208 45 gonçalvesview gonçalvesview PROPN bracis-28402 208 46 author author NOUN bracis-28402 208 47 publications publication NOUN bracis-28402 208 48 search search NOUN bracis-28402 208 49 author author NOUN bracis-28402 208 50 on on ADP bracis-28402 208 51 : : PUNCT bracis-28402 208 52 pubmed pubmed PROPN bracis-28402 208 53     SPACE bracis-28402 208 54 google google PROPN bracis-28402 208 55 scholar scholar PROPN bracis-28402 208 56 rodrigo rodrigo PROPN bracis-28402 208 57 silvaview silvaview PROPN bracis-28402 208 58 author author NOUN bracis-28402 208 59 publications publication NOUN bracis-28402 208 60 search search NOUN bracis-28402 208 61 author author NOUN bracis-28402 208 62 on on ADP bracis-28402 208 63 : : PUNCT bracis-28402 208 64 pubmed pubmed PROPN bracis-28402 208 65     SPACE bracis-28402 208 66 google google PROPN bracis-28402 208 67 scholar scholar NOUN bracis-28402 208 68 corresponding correspond VERB bracis-28402 208 69 author author NOUN bracis-28402 208 70 correspondence correspondence NOUN bracis-28402 208 71 to to ADP bracis-28402 208 72 rodrigo rodrigo PROPN bracis-28402 208 73 silva silva PROPN bracis-28402 208 74 . . PUNCT bracis-28402 209 1 editor editor NOUN bracis-28402 209 2 information information NOUN bracis-28402 209 3 editors editor NOUN bracis-28402 209 4 and and CCONJ bracis-28402 209 5 affiliations affiliation NOUN bracis-28402 209 6 federal federal PROPN bracis-28402 209 7 university university PROPN bracis-28402 209 8 of of ADP bracis-28402 209 9 são são PROPN bracis-28402 209 10 carlos carlos PROPN bracis-28402 209 11 , , PUNCT bracis-28402 209 12 são são PROPN bracis-28402 209 13 carlos carlos PROPN bracis-28402 209 14 , , PUNCT bracis-28402 209 15 brazil brazil PROPN bracis-28402 209 16 murilo murilo PROPN bracis-28402 209 17 c. c. PROPN bracis-28402 209 18 naldi naldi PROPN bracis-28402 209 19 centro centro PROPN bracis-28402 209 20 universitario universitario PROPN bracis-28402 209 21 da da PROPN bracis-28402 209 22 fei fei PROPN bracis-28402 209 23 , , PUNCT bracis-28402 209 24 são são PROPN bracis-28402 209 25 bernardo bernardo PROPN bracis-28402 209 26 do do AUX bracis-28402 209 27 campo campo PROPN bracis-28402 209 28 , , PUNCT bracis-28402 209 29 brazil brazil PROPN bracis-28402 209 30 reinaldo reinaldo PROPN bracis-28402 209 31 a. a. PROPN bracis-28402 209 32 c. c. PROPN bracis-28402 209 33 bianchi bianchi PROPN bracis-28402 209 34 rights right NOUN bracis-28402 209 35 and and CCONJ bracis-28402 209 36 permissions permission NOUN bracis-28402 209 37 reprints reprint NOUN bracis-28402 209 38 and and CCONJ bracis-28402 209 39 permissions permission VERB bracis-28402 209 40 copyright copyright NOUN bracis-28402 209 41 information information NOUN bracis-28402 209 42 © © ADP bracis-28402 209 43 2023 2023 NUM bracis-28402 209 44 the the DET bracis-28402 209 45 author(s author(s NOUN bracis-28402 209 46 ) ) PUNCT bracis-28402 209 47 , , PUNCT bracis-28402 209 48 under under ADP bracis-28402 209 49 exclusive exclusive ADJ bracis-28402 209 50 license license NOUN bracis-28402 209 51 to to ADP bracis-28402 209 52 springer springer NOUN bracis-28402 209 53 nature nature PROPN bracis-28402 209 54 switzerland switzerland PROPN bracis-28402 209 55 ag ag PROPN bracis-28402 209 56 about about ADP bracis-28402 209 57 this this DET bracis-28402 209 58 paper paper NOUN bracis-28402 209 59 cite cite VERB bracis-28402 209 60 this this DET bracis-28402 209 61 paper paper NOUN bracis-28402 209 62 gonçalves gonçalves PROPN bracis-28402 209 63 , , PUNCT bracis-28402 209 64 m.c m.c PROPN bracis-28402 209 65 . . PROPN bracis-28402 209 66 , , PUNCT bracis-28402 209 67 silva silva PROPN bracis-28402 209 68 , , PUNCT bracis-28402 209 69 r. r. PROPN bracis-28402 209 70 ( ( PUNCT bracis-28402 209 71 2023 2023 NUM bracis-28402 209 72 ) ) PUNCT bracis-28402 209 73 . . PUNCT bracis-28402 210 1 the the DET bracis-28402 210 2 effect effect NOUN bracis-28402 210 3 of of ADP bracis-28402 210 4     SPACE bracis-28402 210 5 statistical statistical ADJ bracis-28402 210 6 hypothesis hypothesis NOUN bracis-28402 210 7 testing testing NOUN bracis-28402 210 8 on on ADP bracis-28402 210 9     SPACE bracis-28402 210 10 machine machine NOUN bracis-28402 210 11 learning learn VERB bracis-28402 210 12 model model NOUN bracis-28402 210 13 selection selection NOUN bracis-28402 210 14 . . PUNCT bracis-28402 211 1 in in ADP bracis-28402 211 2 : : PUNCT bracis-28402 211 3 naldi naldi PROPN bracis-28402 211 4 , , PUNCT bracis-28402 211 5 m.c m.c PROPN bracis-28402 211 6 . . PROPN bracis-28402 211 7 , , PUNCT bracis-28402 211 8 bianchi bianchi PROPN bracis-28402 211 9 , , PUNCT bracis-28402 211 10 r.a.c r.a.c ADP bracis-28402 211 11 . . PUNCT bracis-28402 211 12 ( ( PUNCT bracis-28402 211 13 eds ed NOUN bracis-28402 211 14 ) ) PUNCT bracis-28402 211 15 intelligent intelligent ADJ bracis-28402 211 16 systems system NOUN bracis-28402 211 17 . . PUNCT bracis-28402 212 1 bracis bracis PROPN bracis-28402 212 2 2023 2023 NUM bracis-28402 212 3 . . PUNCT bracis-28402 213 1 lecture lecture NOUN bracis-28402 213 2 notes note NOUN bracis-28402 213 3 in in ADP bracis-28402 213 4 computer computer NOUN bracis-28402 213 5 science science NOUN bracis-28402 213 6 ( ( PUNCT bracis-28402 213 7 ) ) PUNCT bracis-28402 213 8 , , PUNCT bracis-28402 213 9 vol vol NOUN bracis-28402 213 10 14196 14196 NUM bracis-28402 213 11 . . PUNCT bracis-28402 214 1 springer springer NOUN bracis-28402 214 2 , , PUNCT bracis-28402 214 3 cham cham PROPN bracis-28402 214 4 . . PUNCT bracis-28402 215 1 https://doi.org/10.1007/978-3-031-45389-2_28 https://doi.org/10.1007/978-3-031-45389-2_28 NOUN bracis-28402 215 2 download download NOUN bracis-28402 215 3 citation citation NOUN bracis-28402 215 4 .ris .ris PUNCT bracis-28402 216 1 .enw .enw PROPN bracis-28402 216 2 .bib .bib PUNCT bracis-28402 217 1 doi doi PROPN bracis-28402 217 2 : : PUNCT bracis-28402 217 3 https://doi.org/10.1007/978-3-031-45389-2_28 https://doi.org/10.1007/978-3-031-45389-2_28 NOUN bracis-28402 217 4 published publish VERB bracis-28402 217 5 : : PUNCT bracis-28402 217 6 12 12 NUM bracis-28402 217 7 october october PROPN bracis-28402 217 8 2023 2023 NUM bracis-28402 217 9 publisher publisher NOUN bracis-28402 217 10 name name NOUN bracis-28402 217 11 : : PUNCT bracis-28402 217 12 springer springer NOUN bracis-28402 217 13 , , PUNCT bracis-28402 217 14 cham cham PROPN bracis-28402 217 15 print print PROPN bracis-28402 217 16 isbn isbn PROPN bracis-28402 217 17 : : PUNCT bracis-28402 217 18 978 978 NUM bracis-28402 217 19 - - SYM bracis-28402 217 20 3 3 NUM bracis-28402 217 21 - - PUNCT bracis-28402 217 22 031 031 NUM bracis-28402 217 23 - - PUNCT bracis-28402 217 24 45388 45388 NUM bracis-28402 217 25 - - SYM bracis-28402 217 26 5 5 NUM bracis-28402 217 27 online online ADJ bracis-28402 217 28 isbn isbn NOUN bracis-28402 217 29 : : PUNCT bracis-28402 217 30 978 978 NUM bracis-28402 217 31 - - SYM bracis-28402 217 32 3 3 NUM bracis-28402 217 33 - - PUNCT bracis-28402 217 34 031 031 NUM bracis-28402 217 35 - - PUNCT bracis-28402 217 36 45389 45389 NUM bracis-28402 217 37 - - SYM bracis-28402 217 38 2 2 NUM bracis-28402 217 39 ebook ebook NOUN bracis-28402 217 40 packages package NOUN bracis-28402 217 41 : : PUNCT bracis-28402 217 42 computer computer NOUN bracis-28402 217 43 sciencecomputer sciencecomputer NOUN bracis-28402 217 44 science science NOUN bracis-28402 217 45 ( ( PUNCT bracis-28402 217 46 r0 r0 NOUN bracis-28402 217 47 ) ) PUNCT bracis-28402 217 48 share share VERB bracis-28402 217 49 this this DET bracis-28402 217 50 paper paper NOUN bracis-28402 217 51 anyone anyone PRON bracis-28402 217 52 you you PRON bracis-28402 217 53 share share VERB bracis-28402 217 54 the the DET bracis-28402 217 55 following follow VERB bracis-28402 217 56 link link NOUN bracis-28402 217 57 with with ADP bracis-28402 217 58 will will AUX bracis-28402 217 59 be be AUX bracis-28402 217 60 able able ADJ bracis-28402 217 61 to to PART bracis-28402 217 62 read read VERB bracis-28402 217 63 this this DET bracis-28402 217 64 content content NOUN bracis-28402 217 65 : : PUNCT bracis-28402 217 66 get get VERB bracis-28402 217 67 shareable shareable ADJ bracis-28402 217 68 linksorry linksorry NOUN bracis-28402 217 69 , , PUNCT bracis-28402 217 70 a a DET bracis-28402 217 71 shareable shareable ADJ bracis-28402 217 72 link link NOUN bracis-28402 217 73 is be AUX bracis-28402 217 74 not not PART bracis-28402 217 75 currently currently ADV bracis-28402 217 76 available available ADJ bracis-28402 217 77 for for ADP bracis-28402 217 78 this this DET bracis-28402 217 79 article article NOUN bracis-28402 217 80 . . PUNCT bracis-28402 218 1 copy copy VERB bracis-28402 218 2 shareable shareable ADJ bracis-28402 218 3 link link NOUN bracis-28402 218 4 to to PART bracis-28402 218 5 clipboard clipboard NOUN bracis-28402 218 6 provided provide VERB bracis-28402 218 7 by by ADP bracis-28402 218 8 the the DET bracis-28402 218 9 springer springer NOUN bracis-28402 218 10 nature nature PROPN bracis-28402 218 11 sharedit sharedit PROPN bracis-28402 218 12 content content NOUN bracis-28402 218 13 - - PUNCT bracis-28402 218 14 sharing share VERB bracis-28402 218 15 initiative initiative NOUN bracis-28402 218 16 keywords keyword NOUN bracis-28402 218 17 machine machine NOUN bracis-28402 218 18 learning learning NOUN bracis-28402 218 19 model model NOUN bracis-28402 218 20 selection selection NOUN bracis-28402 218 21 hypothesis hypothesis NOUN bracis-28402 218 22 testing testing NOUN bracis-28402 218 23 publish publish NOUN bracis-28402 218 24 with with ADP bracis-28402 218 25 us us PROPN bracis-28402 218 26 policies policy NOUN bracis-28402 218 27 and and CCONJ bracis-28402 218 28 ethics ethic NOUN bracis-28402 218 29 search search NOUN bracis-28402 218 30 search search NOUN bracis-28402 218 31 by by ADP bracis-28402 218 32 keyword keyword NOUN bracis-28402 218 33 or or CCONJ bracis-28402 218 34 author author NOUN bracis-28402 218 35 search search NOUN bracis-28402 218 36 navigation navigation NOUN bracis-28402 218 37 find find VERB bracis-28402 218 38 a a DET bracis-28402 218 39 journal journal NOUN bracis-28402 218 40 publish publish VERB bracis-28402 218 41 with with ADP bracis-28402 218 42 us we PRON bracis-28402 218 43 track track VERB bracis-28402 218 44 your your PRON bracis-28402 218 45 research research NOUN bracis-28402 218 46 discover discover VERB bracis-28402 218 47 content content NOUN bracis-28402 218 48 journals journal NOUN bracis-28402 218 49 a a DET bracis-28402 218 50 - - PUNCT bracis-28402 218 51 z z NOUN bracis-28402 218 52 books book NOUN bracis-28402 218 53 a a DET bracis-28402 218 54 - - PUNCT bracis-28402 218 55 z z NOUN bracis-28402 218 56 publish publish NOUN bracis-28402 218 57 with with ADP bracis-28402 218 58 us us PROPN bracis-28402 218 59 journal journal PROPN bracis-28402 218 60 finder finder PROPN bracis-28402 218 61 publish publish VERB bracis-28402 218 62 your your PRON bracis-28402 218 63 research research NOUN bracis-28402 218 64 language language NOUN bracis-28402 218 65 editing edit VERB bracis-28402 218 66 open open ADJ bracis-28402 218 67 access access NOUN bracis-28402 218 68 publishing publishing NOUN bracis-28402 218 69 products product NOUN bracis-28402 218 70 and and CCONJ bracis-28402 218 71 services service NOUN bracis-28402 218 72 our our PRON bracis-28402 218 73 products product NOUN bracis-28402 218 74 librarians librarian VERB bracis-28402 218 75 societies society NOUN bracis-28402 218 76 partners partner NOUN bracis-28402 218 77 and and CCONJ bracis-28402 218 78 advertisers advertiser NOUN bracis-28402 218 79 our our PRON bracis-28402 218 80 brands brand NOUN bracis-28402 218 81 springer springer NOUN bracis-28402 218 82 nature nature PROPN bracis-28402 218 83 portfolio portfolio PROPN bracis-28402 218 84 bmc bmc PROPN bracis-28402 218 85 palgrave palgrave PROPN bracis-28402 218 86 macmillan macmillan PROPN bracis-28402 218 87 apress apress PROPN bracis-28402 218 88 discover discover VERB bracis-28402 218 89 your your PRON bracis-28402 218 90 privacy privacy NOUN bracis-28402 218 91 choices choice NOUN bracis-28402 218 92 / / SYM bracis-28402 218 93 manage manage NOUN bracis-28402 218 94 cookies cookie NOUN bracis-28402 218 95 your your PRON bracis-28402 218 96 us us PROPN bracis-28402 219 1 state state NOUN bracis-28402 219 2 privacy privacy NOUN bracis-28402 219 3 rights right NOUN bracis-28402 219 4 accessibility accessibility NOUN bracis-28402 219 5 statement statement NOUN bracis-28402 219 6 terms term NOUN bracis-28402 219 7 and and CCONJ bracis-28402 219 8 conditions condition NOUN bracis-28402 219 9 privacy privacy NOUN bracis-28402 219 10 policy policy NOUN bracis-28402 219 11 help help NOUN bracis-28402 219 12 and and CCONJ bracis-28402 219 13 support support VERB bracis-28402 219 14 legal legal ADJ bracis-28402 219 15 notice notice NOUN bracis-28402 219 16 cancel cancel VERB bracis-28402 219 17 contracts contract NOUN bracis-28402 219 18 here here ADV bracis-28402 219 19 129.74.145.123 129.74.145.123 NUM bracis-28402 219 20 hesburgh hesburgh PROPN bracis-28402 219 21 library library PROPN bracis-28402 219 22 er er INTJ bracis-28402 219 23 unit unit NOUN bracis-28402 219 24 ( ( PUNCT bracis-28402 219 25 3005732405 3005732405 NUM bracis-28402 219 26 ) ) PUNCT bracis-28402 219 27 northeast northeast ADJ bracis-28402 219 28 research research NOUN bracis-28402 219 29 libraries library NOUN bracis-28402 219 30 ( ( PUNCT bracis-28402 219 31 nerl nerl PROPN bracis-28402 219 32 ) ) PUNCT bracis-28402 219 33 ( ( PUNCT bracis-28402 219 34 8200828607 8200828607 NUM bracis-28402 219 35 ) ) PUNCT bracis-28402 219 36 nerl nerl VERB bracis-28402 219 37 ta ta X bracis-28402 219 38 account account NOUN bracis-28402 219 39 ( ( PUNCT bracis-28402 219 40 3006206169 3006206169 NUM bracis-28402 219 41 ) ) PUNCT bracis-28402 219 42 university university NOUN bracis-28402 219 43 of of ADP bracis-28402 219 44 notre notre PROPN bracis-28402 219 45 dame dame PROPN bracis-28402 219 46 hesburgh hesburgh PROPN bracis-28402 219 47 library library NOUN bracis-28402 219 48 ( ( PUNCT bracis-28402 219 49 3000184373 3000184373 NUM bracis-28402 219 50 ) ) PUNCT bracis-28402 220 1 © © ADP bracis-28402 220 2 2025 2025 NUM bracis-28402 220 3 springer springer NOUN bracis-28402 220 4 nature nature NOUN