The thesis adopts principal component analysis and Bayesian k nearest neighbour algorithm in forecast of students' future occupations. The students' achievements are used as feature data and principal component analysis is used to reduce the dimensions of feature data.
本文在毕业生就业方向预测中采用了主成分分析和贝叶斯k近邻分类法,采用毕业生成绩作为特征数据,通过主成分分析降低特征数据维数,通过贝叶斯k近邻算法实现分类即职业方向预测。
参考来源 - 基于贝叶斯k近邻和主成分分析的教务数据挖掘研究·2,447,543篇论文数据,部分数据来源于NoteExpress
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