Research on Teaching Evaluation Model Based on Weighted Naive Bayes

Aiming at the problem that the index weight distribution of teaching evaluation system is not objective, and the evaluation method cannot feedback the evaluation result in time, a method of constructing a teaching evaluation model based on weighted naive bayes algorithm is proposed. Firstly, a large amount of actual data of students' teaching evaluation was collected and sorted out, and data mining technology was adopted to realize data preprocessing of evaluation data. Secondly, the evaluation value was mapped into different grades, and a classifier based on weighted naive bayes algorithm was established. Finally, the classifier was used to assign different weights to each evaluation index, and the teaching evaluation results could be given in time through the classifier. The experimental results show that compared with the traditional teaching evaluation method, the evaluation model has better classification performance and the classification accuracy can reach 0.75. Therefore, this method can provide a reasonable scientific technical reference for teaching evaluation.