An Online Integrated Classification Algorithm for Innovation and Entrepreneurship Teaching Data Based on Decision Tree

In order to improve the accuracy of data classification, reduce misclassification rates, and improve classification efficiency, a decision tree based online integrated classification algorithm for innovation and entrepreneurship teaching data is proposed. Establish a prototype system for online integration of innovation and entrepreneurship teaching data, and based on the results of data integration, preliminarily construct a decision tree model. Then, the fuzzy decision tree obtained by combining fuzzy theory with decision tree is used to solve the problems of data imbalance and missing data types. In order to further reduce the misclassification rate of data, the differential grey wolf optimization algorithm is used to optimize the decision tree, and the decision tree is improved through operations such as feature selection and decision tree pruning to obtain the optimal classification results of innovation and entrepreneurship teaching data. The experimental results show that the proposed method has high data classification accuracy, low misclassification rate, and high classification efficiency, which verifies the effectiveness of the method.