Evaluating and Classifying NBA Free Agents
نویسنده
چکیده
In this project, I applied machine learning techniques to perform multiclass classification on free agents by using game statistics, which is useful to evaluate players’ performances. To do so, I implemented and compared a collection of supervised and unsupervised learning algorithms on a dataset consisting of 282 free agent samples. No previous work was accessible, and depending on the features I selected, Naïve Bayes outperformed the other algorithms and achieved an accuracy of 76%.
منابع مشابه
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