Construction of College Students' Integrity Evaluation Model Based on Bayesian Classifier

Abstract

The information classification and statistical feature extraction methods are used to design the evaluation model of college students' honesty and credit, and a new model based on Bayesian classifier is proposed to evaluate the integrity of college students. The data of credit evaluation come from college students' records of returning books, credit card records, cheating records, records of violation of discipline, and records of class. The multisource statistical recursive analysis model is used to deal with the data fusion of college students' credit evaluation, and the characteristic quantity of multi-source information fusion which reflects the integrity of college students is extracted. The extracted feature information is processed by data clustering, and the data clustering is implemented by Bayesian classifier, and the reliability and robustness of the evaluation model are tested and analyzed by the quantitative recursive analysis and grouping sample test. The empirical analysis and simulation results show that the reliability, objectivity and confidence of the evaluation results are good.