id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
ajet-2307	Heritier Nsenge, Mpia; Mystere Kivuyirwa, Kanduki; Ange Katya, Kitakya	Deep Learning for Predicting University Academic Fees in a Semi-Urban Area	2023	10	.pdf	application/pdf	5650	319	52	In the process of descriptive statistics for these variables, the authors studied the correlation between the target variable (Frais_ Academique) and the Promotion variable, as summarized in the following figure 3 14 Internet Internet fees 10, 30, 35 15 Carte_etudiant Student card fees 5 16 Edition_Ishango Ishango edition fees 6, 5, 4 17 Frais_ academiques Academic fees 350,500,435,600,540,700,345,360,305,440,605,390, 52 5,450,630,505,365,385,340,495,430,595,480,650, 355,5 20,445,625,380,545,475,535,485,575,490,510, 474,524, 339,344,429,544,354,479,434,384,499,444, 574 Figure 2: Distribution of Promotion variable Figure 3: Correlation between academic fees and promotion From the figure 3 results, the authors observe that academic fees are correlated to promotion. Published: December 25, 2023 Academic fees are an annual amount that students must pay in return for the training they receive.	cache/ajet-2307.pdf	txt/ajet-2307.txt