Construction of a Talent Quality Evaluation Model for Long Distance Running Clubs in Vocational Colleges under the Background of"Three Comprehensive Education"
In the context of"comprehensive education",the teaching quality of sports and arts has been valued.There is currently no suitable model for evaluating the quality of talent in long-distance running clubs on the internet.In this study,a talent quality evaluation model for long-distance running clubs is proposed based on feature weighted clustering algorithm.Used fuzzy K-prototype clustering as the core algorithm is the model,and in order to improve evaluation accuracy,a feature weighting algorithm is introduced for optimization.In addition,it was found in the study that the model runs slowly and is difficult to achieve global optimization,so the mountain climbing algorithm is used to improve the convergence speed of the model.The experimental results show that the model has an evaluation accuracy of 93.16%,a clustering purity of 87.07%,and an average output time of 50.03 seconds on a self created dataset.Compared with other similar models,this model is progressiveness in terms of running time,evaluation accuracy,clustering effect,etc.
Three comprehensive educationQuality assessmentLong distance runningFKPFeature weighting