现代电子技术2024，Vol.47Issue(2)：49-54,6.DOI:10.16652/j.issn.1004-373x.2024.02.010
基于统计学习算法的学生就业服务平台数据分类方法
Method of student employment service platform data classification based on statistical learning algorithm
摘要
Abstract
Student employment is the core of higher education quality management,and the student employment service platform is a new method to solve students'employment difficulties.In order to better provide employment services for students,a method of student employment service platform data classification based on statistical learning algorithm is proposed.The characteristic attributes of the data sample of the student employment service platform is selected by means of the information entropy and information gain indicators.The principal component analysis method is used to integrate the characteristic information of the sample data of the student employment service platform.On this basis,the naive Bayesian algorithm based on statistical learning algorithm is used to input the characteristic information of the fused sample data of the student employment service platform to the naive Bayesian classifier model,and the data classification of the student employment service platform is realized by combining the prior probability with posterior probability.The experimental results show that the ROC curve area of the proposed method is more than 98%of the overall effective area,the classification accuracy rate is up to 95.8%,and the classification time is only 5.38 ms,which has a good data classification effect on the student employment service platform,can improve the classification accuracy,and can effectively shorten the classification time.关键词
统计学习算法/学生就业/服务平台/数据分类/朴素贝叶斯算法/信息熵Key words
statistical learning algorithm/student employment/service platform/data classification/naive Bayesian algorithm/information entropy分类
电子信息工程引用本文复制引用
蒋大锐,徐胜超..基于统计学习算法的学生就业服务平台数据分类方法[J].现代电子技术,2024,47(2):49-54,6.基金项目
国家自然科学基金面上项目(61772221) （61772221）
广州华商学院校内导师制科研项目资助(2023HSDS08) （2023HSDS08）
