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Optimization of sports effect evaluation technology from random forest algorithm and elastic network algorithm.

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This study uses machine learning, including Elastic Net and Random Forest algorithms, to assess how different sports impact physical health, creating a better tool for sports selection and health promotion.

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Area of Science:

  • Sports Science
  • Data Mining
  • Machine Learning

Background:

  • Understanding the impact of sports on physical health is crucial for effective health promotion and informed sports selection.
  • Existing methods for sports performance assessment may not fully capture the nuanced effects of diverse physical activities.

Purpose of the Study:

  • To develop and validate a robust sports performance assessment model using advanced data mining and machine learning.
  • To identify key factors influencing physical health indicators across various sports categories.
  • To provide a scientific basis for optimizing sports engagement for health benefits.

Main Methods:

  • Construction of a sports performance assessment model guided by the Elastic Net algorithm for feature selection.
  • Integration of the Random Forest algorithm for comprehensive sports performance evaluation across dimensions like wrestling, soccer, skill-based sports, and physical education.
  • Comparative analysis of model accuracy using the Top-K criterion (Top-3, Top-5, Top-10) against the Support Vector Machine (SVM) algorithm.

Main Results:

  • The combined Elastic Net and Random Forest approach provides a more precise assessment of sports' effects on physical health indicators compared to conventional methods.
  • The model effectively identifies crucial influencing factors for diverse sports activities.
  • The study demonstrates the efficacy of the developed model in evaluating sports performance and health impacts.

Conclusions:

  • The integrated Elastic Net and Random Forest methodology offers a significant advancement in sports performance assessment and health development tools.
  • This research provides valuable insights into the differential impacts of various sports on physical health.
  • The findings support evidence-based sports selection and personalized health promotion strategies.