D. Thenmozhi, P. Mirunalini, S. M. Jaisakthi, Srivatsan Vasudevan, V. Veeramani Kannan, S. Sagubar Sadiq
{"title":"MoneyBall -对板球数据集的数据挖掘","authors":"D. Thenmozhi, P. Mirunalini, S. M. Jaisakthi, Srivatsan Vasudevan, V. Veeramani Kannan, S. Sagubar Sadiq","doi":"10.1109/ICCIDS.2019.8862065","DOIUrl":null,"url":null,"abstract":"Cricket is one of the most popular sports in the whole world, and also one of the most popular sports in India. Cricketing events such as the Indian Premier League (IPL) are thoroughly enjoyed by fans all across the country. Fans of the game love predicting the ongoing match results, and this is something that has ended up being a hobby for several people who follow the game. This is a sport with abundant amount of data and using this data, we can make an evaluation on whether a team can win an ongoing IPL match or not. This prediction is implemented by using machine learning algorithms such as Gaussian Naive Bayes, Support Vector Machine, K-Nearest Neighbor and Random Forest. The required dataset is obtained by collecting using a website and consolidated. As a result, the output is obtained which lists whether the home team has won the match or not. The accuracies obtained are 75%, 80%, 55%, 75%, 80%, 80%, 75% and 84% for the teams CSK, RR, DD, RCB, MI, SRH, KXIP and KKR respectively.","PeriodicalId":196915,"journal":{"name":"2019 International Conference on Computational Intelligence in Data Science (ICCIDS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"MoneyBall - Data Mining on Cricket Dataset\",\"authors\":\"D. Thenmozhi, P. Mirunalini, S. M. Jaisakthi, Srivatsan Vasudevan, V. Veeramani Kannan, S. Sagubar Sadiq\",\"doi\":\"10.1109/ICCIDS.2019.8862065\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cricket is one of the most popular sports in the whole world, and also one of the most popular sports in India. Cricketing events such as the Indian Premier League (IPL) are thoroughly enjoyed by fans all across the country. Fans of the game love predicting the ongoing match results, and this is something that has ended up being a hobby for several people who follow the game. This is a sport with abundant amount of data and using this data, we can make an evaluation on whether a team can win an ongoing IPL match or not. This prediction is implemented by using machine learning algorithms such as Gaussian Naive Bayes, Support Vector Machine, K-Nearest Neighbor and Random Forest. The required dataset is obtained by collecting using a website and consolidated. As a result, the output is obtained which lists whether the home team has won the match or not. The accuracies obtained are 75%, 80%, 55%, 75%, 80%, 80%, 75% and 84% for the teams CSK, RR, DD, RCB, MI, SRH, KXIP and KKR respectively.\",\"PeriodicalId\":196915,\"journal\":{\"name\":\"2019 International Conference on Computational Intelligence in Data Science (ICCIDS)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Computational Intelligence in Data Science (ICCIDS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIDS.2019.8862065\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Computational Intelligence in Data Science (ICCIDS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIDS.2019.8862065","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cricket is one of the most popular sports in the whole world, and also one of the most popular sports in India. Cricketing events such as the Indian Premier League (IPL) are thoroughly enjoyed by fans all across the country. Fans of the game love predicting the ongoing match results, and this is something that has ended up being a hobby for several people who follow the game. This is a sport with abundant amount of data and using this data, we can make an evaluation on whether a team can win an ongoing IPL match or not. This prediction is implemented by using machine learning algorithms such as Gaussian Naive Bayes, Support Vector Machine, K-Nearest Neighbor and Random Forest. The required dataset is obtained by collecting using a website and consolidated. As a result, the output is obtained which lists whether the home team has won the match or not. The accuracies obtained are 75%, 80%, 55%, 75%, 80%, 80%, 75% and 84% for the teams CSK, RR, DD, RCB, MI, SRH, KXIP and KKR respectively.
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