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Evaluation research on data processing of mental health of college students based on decision tree algorithm

机译:基于决策树算法的大学生心理健康数据处理评价研究

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With the popularization of higher education in China, a series of social problems caused by mental health problems rise frequently because of the imperfect mental quality of college students, attracting attention of the school and society. To gain insight into the main mental symptoms and factors affecting their mental health, decision tree owns an incomparable advantage, which is an important means in data mining. In this study, methods and procedures of decision tree construction were introduced and decision tree C4.5 algorithm was elaborated. In this algorithm, appropriate attributes were selected as tree roots and subtree roots, and then the decision tree was constructed through repetition. Decision tree algorithm could classify the mental health of college students precisely, analyze rules and guide mental health counselors with correct plans, which was helpful to the decision making and mental health of college students improving.
机译:随着中国高等教育的普及,精神健康问题引起的一系列社会问题经常由于大学生的不完美精神素质,吸引了学校和社会的注意力。要深入了解影响他们心理健康的主要精神症状和因素,决策树拥有一个无与伦比的优势,这是数据挖掘的重要手段。在本研究中,引入了决策树结构的方法和程序,并阐述了决策树C4.5算法。在该算法中,选择了适当的属性作为树根和子树根,然后通过重复构建决策树。决策树算法可以准确地对大学生的心理健康进行分析,分析规则和指导心理健康辅导员,正确的计划,这有助于提高大学生的决策和心理健康。

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