Selecting Optimal Subset of Features for Student Performance Model
作者： Malaka A. Moustafa , Hany M. Harb
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摘要: Educational data mining (EDM) is a new growing research area and the essence of concepts are used in educational field for purpose extracting useful information on student behavior learning process. Classification methods like decision trees, rule mining, Bayesian network, can be applied predicting performance an examination. This prediction may help evaluation. As feature selection influences predictive accuracy any model, it essential to study elaborately effectiveness model connection with techniques. The main objective this work achieve high by adopting various techniques increase least number features. outcomes show reduction computational time constructional cost both training classification phases model.
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