期刊名称：Indian Journal of Computer Science and Engineering
印刷版ISSN：2231-3850
电子版ISSN：0976-5166
出版年度：2019
卷号：10
期号：1
页码：31-34
DOI：10.21817/indjcse/2019/v10i1/191001009
出版社：Engg Journals Publications
摘要：The higher education institutes use data mining tools and techniques for academicimprovement of the student performance and to prevent drop out. The data consists of socio-economic,demographic as well as academic information of three hundred students with 22 attributes. Five ensembleclassification methods Attribute Selected Classifier, Bagging, Classification Via Regression, WeightedInstances Handler Wrapper and Multi Class Classifier were used. The Class Attendance Percentageattribute makes the highest impact in the final semester results of the students in our dataset. The resultsshowed that MultiClassClassifier outperforms the other classifiers based on accuracy and classifiererrors.
关键词：Attribute Selected Classifier; Bagging; Classification Via Regression; Weighted Instances Handler;Wrapper and Multi Class Classifier;
