改进的多叉决策树在大学专业选择系统的应用

Application of Improved Multi-Forks Decision Tree to Major Selection System

考生在高考后对大学专业的选择是其职业生涯的起点。大学专业选择系统可以测定考生的人格特性,根据以往大量数据中提取的模型帮助他们选择适合自身的专业。借助平面向量参考系改进的决策树算法,可以挖掘出训练集中隐含的规则,构建高精度的评判模型,从而避免了以往利用专家系统的方法构建时过分依赖先验知识所产生的误差,更客观的为考生匹配适合的专业。实验证明,算法的挖掘精度和效率都达到了令人满意的效果。

It＇s a starting point of career for the students who have passed the college entrance examination to choose a major.Major Selection System can check the real personality trait and then help select the matching major based on the data obtained.This study improves data mining algorithms by putting the plane vector reference system into it and digs out the implied relevance in the sample set to build the measure system.In this way,the inaccuracy of previous expert systems can almost be avoided so that the major can match the students more objectively.Experiments show that the precision and efficiency of the algorithms are almost satisfactory.