淡江大學機構典藏:Item 987654321/116860
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 62816/95882 (66%)
造访人次 : 3995985      在线人数 : 636
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧：
  • 您可在西文检索词汇前后加上"双引号"，以获取较精准的检索结果
  • 若欲以作者姓名搜寻，建议至进阶搜寻限定作者字段，可获得较完整数据
    •  进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/116860


    题名: Predicting Yearly Winning Percentage of MLB Teams by Regression Trees
    作者: Jou, Chichang;Lo, Li-wen
    关键词: MLRT;CART;Winning;Percentage Prediction;Playoff Prediction;MAPE;MLB
    日期: 2019-04-06
    上传时间: 2019-06-15 12:10:44 (UTC+8)
    摘要: Major League Baseball of the USA is considered the most competitive and challenging arena of baseball. And the population of baseball fans is still increasing. Many scholars and fans are interested in using each team’s performance data to predict outcomes of MLB games. Their prediction accuracy is around 50%. Our goal is to use performance data to predict the yearly winning percentage of each team. Our research method is Classification and Regression Trees (CART) and Maximum Likelihood Regression Trees (MLRT). In addition, we will discuss the prediction accuracy of the CART and MLRT models, and apply the result to predict the playoffs list of the MLB. We find that these models all have good prediction effectiveness for the yearly winning percentage with the MAPE between 12% and 13%. CART models are slightly better than MLRT models in winning percentage prediction. For the playoffs prediction, MLRT is only better than CART in 2018 for models eliminating collinear variables. The prediction effectiveness of CART is the same or better than the MLRT for the rest.
    显示于类别:[資訊管理學系暨研究所] 會議論文

    文件中的档案:

    档案 大小格式浏览次数
    index.html0KbHTML194检视/开启

    在機構典藏中所有的数据项都受到原著作权保护.

    TAIR相关文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈