Analysis of physical training performance data based on decision tree

Abstract

Under the background of the current information age, the scientific, accurate and high efficiency of sports training effect evaluation is very important to improve the quality of physical exercise. However, the traditional manual evaluation method is limited by subjective and objective factors, which is often difficult to accurately reflect the training status of the students. This paper aims to solve the inaccurate and time-consuming problems in the evaluation of sports training performance, which has important practical significance and application value. Through the visualization technology to reveal the changes of the training performance, and the modeling and prediction combined with the decision tree algorithm, the accurate estimation of the training performance of the students can be realized, providing strong support for the training feedback and effect improvement.