Efficient approach in cricket team selection methodology using machine learning-based naive bayes algorithm and comparing with random forest algorithm
Abstract
Aim: The proposed machine learning algorithm aims to select the best 11 cricket players in the present Indian test match squad. Methods and materials: Naive Bayes and Random Forest Algorithm are used in this method for the selection of best players in the team. The sample size is 20 from each group and the total sample size is 40 collected from espncricinfo.com. Results: It is observed that Naive Bayes Algorithm has better accuracy (82%) in predicting the team than the Random Forest Algorithm (70%). Conclusion: It is very clear that Naive Bayes Algorithm has better accuracy in selecting the team than the Random Forest Algorithm.
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