Bayesian Classifier Applied to Higher Education Dropout
Amelec Viloria, Omar Bonerge Píneda Lezama, Noel Varela · Procedia Computer Science · 2019
The research proposes a new simple Bayesian classifier (SBND) with Markov from the class variable to a network structure. Experimental tests are carried out by working a dropout analysis on students enrolled in the Faculty of Engineering Sciences of Mumbai University, in India in the period 2017-2018 on the basis of socioeconomic data. The Weka tool is then used to perform the classification and the proposed model is statistically compared with other Bayesian classifiers.