Evaluating Machine Learning Varieties for NBA Players Winning Contribution
學年 106
學期 2
發表日期 2018-06-28
作品名稱 Evaluating Machine Learning Varieties for NBA Players Winning Contribution
作品名稱（其他語言） English
著者 P. Hsu; S. Galsanbadam; Jr-Syu Yang; C. Yang
作品所屬單位
出版者
會議名稱 IEEE ICSSE 2018 Internation Conference on System Science and Engineering
會議地點 National Taipei University, New Taipei City, Taiwan.
摘要 The reputation of NBA breach its boundary worldwide and have numerous fans around all the world. As the league concerns a lot of money and fans, several of researches have been challenged trying to predict its results and winning teams. Through its history a lot of data and statistics are collected for NBA and it’s still becoming more rich and detailed. Even though, such enormous data available, it is still complicated to analyze and predict the outcome of match. In order to achieve exceptional prediction rating we will be focusing on how individual player’s achievement influences the team win rating. For our learning techniques, we choose SVR, polynomial regression and random forest regression as they are able to give consistent result regardless of complex data features.
關鍵字 Maching Learning
語言 en
收錄於
會議性質 國際
校內研討會地點 無
研討會時間 20180628~20180630
通訊作者 Chan-Yun Yang
國別 TWN
公開徵稿
出版型式
出處 ICSSE 2018
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/115703 )