Evaluation of teaching quality based on binary tree support vector machine
Xinghui Wu, Zaifeng Shi, Haihua Xing, Yisheng Xue · MATEC Web of Conferences · 2022
In order to solve the reliability of the evaluation results of teaching quality in universities and colleges, an improved model of teaching evaluation based on the Support vector machine was put forward. In this model, the evaluator does not need to give an evaluation result of the teacher’s teaching quality, but gives the score of each evaluation index, and then calls the Support vector machine, automatic classification of teachers’ teaching quality. The experiment proves that the improved algorithm can improve the teaching quality evaluation accuracy and the result is better.