文章基本信息

标题：Increased Prediction Accuracy in the Game of Cricket Using Machine Learning
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作者：Kalpdrum Passi ; Niravkumar Pandey
期刊名称：International Journal of Data Mining & Knowledge Management Process
印刷版ISSN：2231-007X
电子版ISSN：2230-9608
出版年度：2018
卷号：8
期号：2
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Player selection is one the most important tasks for any sport and cricket is no exception. The performanceof the players depends on various factors such as the opposition team, the venue, his current form etc. Theteam management, the coach and the captain select 11 players for each match from a squad of 15 to 20players. They analyze different characteristics and the statistics of the players to select the best playing 11for each match. Each batsman contributes by scoring maximum runs possible and each bowler contributesby taking maximum wickets and conceding minimum runs. This paper attempts to predict the performanceof players as how many runs will each batsman score and how many wickets will each bowler take for boththe teams. Both the problems are targeted as classification problems where number of runs and number ofwickets are classified in different ranges. We used naïve bayes, random forest, multiclass SVM and decisiontree classifiers to generate the prediction models for both the problems. Random Forest classifier wasfound to be the most accurate for both the problems.
关键词：Naïve Bayes; Random Forest; Multiclass SVM; Decision Trees; Cricket