Decision Tree Algorithm in the Performance Evaluation of School-Enterprise Cooperation for Higher Vocational Education

Abstract

With the development of China’s economy and the internet, machine learning has become one of the people’s favorite ways of working. This study aims to solve the problems of brain drain, inefficiency, and injustice in the performance appraisal of school-enterprise cooperation. Decision tree technology is used to establish an assessment system. After the assessment index data are segmented, and the fuzzy version of the C4.5 algorithm is used to calculate and count different data segments. Finally, different data types are used to classify and construct decision trees. The school-enterprise cooperation performance appraisal system has been established and perfected for higher vocational education. In this way, the performance appraisal system is optimized in the school-enterprise cooperation. The system improves work efficiency while reducing manual labor and improves the problems in the performance appraisal of other colleges and universities’ cooperation. Facts have proved that the establishment of decision trees can effectively solve the problems of duplication of indicators and complex calculations in performance appraisal. After being optimized, the C4.5 algorithm will increase the calculation accuracy to 95%. The overall speed of establishment is increased by 5% based on the algorithm before optimization. This breaks the traditional performance appraisal system and promotes the performance appraisal of school-enterprise cooperation to be more open, transparent, fair, and equal.