Research on the Evaluation Model of Volleyball Training Effectiveness Based on Information Gain and Random Forest Algorithm
In order to effectively evaluate the effectiveness of volleyball,an intelligent evaluation method is proposed.Firstly,the random forest algorithm is used to extract motion features,and the recognition of motion features is achieved by constructing a decision tree and information gain.Considering the parameterization problem faced by the random forest algorithm,the particle swarm optimization algorithm is introduced for model parameter optimization.In the comparison of training effects among different models,the proposed model performs best in the comparison of recall rates,with an average recall rate of 0.978,which is superior to other models.In the comparison of volleyball sports effects,the proposed model evaluated all 8 main indicators above 0.935.In addition,the proposed model performs best in terms of error and time comparison.The proposed intelligent evaluation technology provides technical reference for evaluating the effectiveness of sports such as volleyball and managing the health of the elderly population.
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