id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
ajmsi-1979	Ali, Khizra; Saqib, Muhammad	Risk Prediction of Thalassemia Using Data Mining Classifiers	2023	14	.pdf	application/pdf	7416	392	54	For the evaluation of different data mining algorithms in this research, the dataset was divided into 10-fold cross- Figure 9: J48 Results Table 4: J48 Classifier Output Results using WEKA Tool MCV HCT HGB MCHC RDW Gender ‘prediction margin’ ‘predicted Status’ 66.4 4.9 22.3 29.5 31.5 2 1 POSITIVE 74.6 4.9 19.3 22.6 33.7 1 1 POSITIVE 69 9.3 21.7 26.7 32.6 1 1 POSITIVE 73.1 7.4 25.8 32 26.4 2 1 POSITIVE 77.3 6.8 34.2 31.3 33.6 1 1 POSITIVE 71.2 6.8 21.5 30.1 36.7 1 1 POSITIVE 80.1 10.5 11.6 35.2 42.1 1 -0.974359 For the evaluation of different data mining algorithms in this research, the dataset was categorised into 10-fold cross-validation.	cache/ajmsi-1979.pdf	txt/ajmsi-1979.txt