A Study of Tennis Score Evaluation Based on Logistic Regression and LSTM Neural Networks

Abstract

In order to study the performance of athletes in the competition, this paper establishes a comprehensive evaluation mechanism and prediction model through mathematical modeling. Firstly, this paper uses the clustering algorithm to categorize the data and establishes a score evaluation model according to the weights. Then, a momentum evaluation score calculation function was constructed and compared with the results of logistic regression algorithm. Finally, a multi-indicator data system was established to predict the results of the game using the LSTM neural network model. The experimental results show that the model proposed in this paper has a good prediction effect and provides suggestions to the participants.