Classification Decision Tree Algorithm in Predicting Students’ Course Preference

Zhaolong Gao, Mengvi P. Gatpandan, Paulino H. Gatpandan
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Abstract

With the continuous development of machine learning, more and more applications are applied to all areas of life. Decision tree algorithm, as a classic algorithm in machine learning, is also widely used in various industries. In recent years, the informatization of the college entrance examination has allowed the admissions department to accumulate a large amount of college entrance examination data. Based on the decision tree algorithm in machine learning, the candidate data is analyzed, and an algorithm for predicting candidates to apply for the major is proposed, and the admission data of a certain university in Yantai is used as an experiment. The data set tests the prediction accuracy of the algorithm. Two complete decision trees have been constructed to provide high school seniors with intelligent decisions and suggestions for a series of basic issues such as college selection, major selection, and voluntary reporting.
分类决策树算法预测学生课程偏好
随着机器学习的不断发展,越来越多的应用被应用到生活的各个领域。决策树算法作为机器学习中的经典算法,也被广泛应用于各个行业。近年来,高考的信息化让招生部门积累了大量的高考数据。基于机器学习中的决策树算法,对考生数据进行分析,提出了一种预测报考考生的算法,并以烟台某高校的录取数据作为实验。数据集测试了算法的预测精度。构建了两棵完整的决策树,为高三学生在大学选择、专业选择、志愿报告等一系列基本问题上提供智能决策和建议。
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