Decision tree algorithm has been widely used in the diagnosis, evaluation and classification of table tennis games, and its advantages in the diagnosis of game techniques and tactics have emerged, but there is a lack of systematic scientific research on the model of diagnosis, evaluation and classification. In order to solve the shortcomings of the existing research on diagnosis, evaluation and classification of techniques in table tennis, this paper discusses the steps of ID3 algorithm to build decision tree and discusses the scoring rate and usage rate in table tennis as well as the evaluation of techniques and tactics in table tennis, and then discusses the construction of tactical index system and discretization of winning probability of decision tree algorithm for the application of tactical diagnosis and classification model in table tennis. A brief discussion is given on the construction of a tactical index system and the discretization of the probability of winning by decision tree algorithm. And the design of the decision tree algorithm in the table tennis game tactical classification model is discussed, and the decision tree algorithm is used to classify and diagnose three tactical categories, and the experimental data show that the algorithm has an average correct rate of 97.1% for the tactical classification in the serve, receive and hold sections. Therefore, it is verified that the decision tree algorithm has a high practical value in the technical and tactical classification diagnosis of table tennis matches.

Nian Zhang. About Decision Tree Algorithm in Table Tennis Tournament. Machine Learning Theory and Practice (2020), Vol. 1, Issue 4: 17-25. https://doi.org/10.38007/ML.2020.010403.

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