Prediction of Student Performance Through an Intelligent Hybrid Model
作者： Héctor Alaiz-Moretón , José Antonio López Vázquez , Héctor Quintián , José-Luis Casteleiro-Roca , Esteban Jove
DOI: 10.1007/978-3-030-29859-3_60
关键词: Artificial intelligence 、 Machine learning 、 Computer science 、 Regression 、 Cluster analysis 、 Hybrid model 、 Linear discriminant analysis 、 Global model 、 Visualization
摘要: The present work addresses the problem of low academic performance in engineering degree students. Models capable predicting are generated through application several intelligent regression techniques to a dataset containing official records students University A Coruna. global model, specifically hybrid model based on K-means clustering, can predict grade subject previous courses. In addition, an LDA (Linear Discriminant Analysis) has been implemented order identify important features and visualize classification clearly. Thus, developed makes it possible estimate each student as well most variables associated with it.
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