Prediction of the Scholarship Using Comprehensive Development

Wenjuan Wei, Jiaxin Han, Jie Kong, Haiyang Xia
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引用次数: 5

Abstract

In major colleges and universities, in order to mobilize students enthusiasm for studying and participating in extracurricular activities, all colleges make an evaluation on students comprehensive quality and set different rewards regulations for the various level. The main way is to provide financial incentives, they distribute scholarship for students of meeting requirements. The Decision Tree algorithm is frequently used all the time, however, because of the tree node selected is based on attribute's mutual information, which will lead to some crucial attribute lost their decisive role. Therefore, in this paper, we focused on predicting whether students obtain scholarship on the comprehensive quality of students with Naive Bayes algorithm.
基于综合发展的奖学金预测
在各大高校,为了调动学生学习和参加课外活动的积极性,各学院都对学生的综合素质进行评价,并对各级学生制定了不同的奖励规定。主要方式是提供经济奖励,他们为符合要求的学生发放奖学金。决策树算法一直被频繁使用,但由于树节点的选择是基于属性的互信息,这将导致一些关键属性失去其决定性作用。因此,在本文中,我们将重点放在用朴素贝叶斯算法来预测学生是否获得奖学金上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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