Web Based Genetic Algorithm Using Data Mining
Journal Title: American journal of Engineering Research - Year 2016, Vol 5, Issue 9
Abstract
This paper presents an approach for classifying students in order to predict their final grade based on features extracted from logged data in an education web-based system. A combination of multiple classifiers leads to a significant improvement in classification performance. Through weighting the feature vectors using a Genetic Algorithm we can optimize the prediction accuracy and get a marked improvement over raw classification. It further shows that when the number of features is few; feature weighting is works better than just feature selection. Many leading educational institutions are working to establish an online teaching and learning presence. Several systems with different capabilities and approaches have been developed to deliver online education in an academic setting. In particular, Michigan State University (MSU) has pioneered some of these systems to provide an infrastructure for online instruction. The research presented here was performed on a part of the latest online educational system developed at MSU, the Learning Online Network with Computer-Assisted Personalized Approach (LON-CAPA).
Authors and Affiliations
Ashiqur Rahman1, Asaduzzaman Noman2 ,, Md. Ashraful Islam3 ,, Al-Amin Gaji4
Keywords
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