利用naÏve贝叶斯算法对高中生进行预测的进一步研究

None Siti Nur Amalia, Maulana Wildan Rifaldi, Mega Aprilia Fajriati, Rona Nisa Sofia Amriza
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引用次数: 0

摘要

拥有大量学生继续学习大学的学校将成为从小学到中学的主要选择。因此,增加学生继续学习的数量对于应对竞争是非常重要的。为了解决这个问题,学校可以预测高中/职业高中学生在大学的学习。目标是预测结果的百分比可以作为提高学校教育服务质量的参考。在进行这种预测时,使用Naïve贝叶斯方法或算法。在这种情况下,Naïve贝叶斯算法是一种具有概率和统计方法的分类方法,适用于预测高中/职业高中学生升入大学的学习情况。利用Naïve贝叶斯对测试数据进行大学继续学习的预测结果准确率为0.740。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
THE USE OF NAÏVE BAYES ALGORITHM IN FORECASTING THE FURTHER STUDY OF HIGH SCHOOL STUDENT
Schools with a large number of students who continue their studies to college will be the main choice as secondary schools from the elementary level. Therefore, increasing the number of students continuing their studies is very important to meet the competition. To get around this, schools can predict the continuation of high school/vocational high school students' studies to college. The goal is that the percentage of prediction results can be used as a reference for improving the quality of education services in schools. In making this prediction, the Naïve Bayes method or algorithm is used. In this case, the Naïve Bayes algorithm is a classification method with a probability and statistical approach that is suitable for predicting the continuation of high school/vocational high school students' studies to college. The prediction result of continuing study to university using Naïve Bayes on test data has an accuracy of 0.740.
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