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T. Menzies, O. Mizuno, Y. Takagi, and T. Kikuno, "Explanation Vs Performance in Data Mining: a Case Study with Predicting Runaway Projects," Journal of Software Engineering and Applications, 2(4), pp. 221-236, November 2009.
ID 544
分類 学術論文誌(査読付)
タグ case data explanation mining performance predicting projects runaway study 国際共著
表題 (title) Explanation Vs Performance in Data Mining: a Case Study with Predicting Runaway Projects
表題 (英文)
著者名 (author) Tim Menzies,Osamu Mizuno,Yasunari Takagi,Tohru Kikuno
英文著者名 (author) Tim Menzies,Osamu Mizuno,Yasunari Takagi,Tohru Kikuno
キー (key) Tim Menzies,Osamu Mizuno,Yasunari Takagi,Tohru Kikuno
定期刊行物名 (journal) Journal of Software Engineering and Applications
定期刊行物名 (英文)
巻数 (volume) 2
号数 (number) 4
ページ範囲 (pages) 221-236
刊行月 (month) 11
出版年 (year) 2009
Impact Factor (JCR)
URL doi:10.4236/jsea.2009.24030
付加情報 (note)
注釈 (annote)
内容梗概 (abstract) Often, the explanatory power of a learned model must be traded off against model performance. In the case of predicting runaway software projects, we show that the twin goals of high performance and good explanatory power are achievable after applying a variety of data mining techniques (discrimination, feature subset selection, rule covering algorithms). This result is a new high water mark in predicting runaway projects. Measured in terms of precision, this new model is as good as can be expected for our data. Other methods might out-perform our result (e.g. by generating a smaller, more explainable model) but no other method could out-perform the precision of our learned model.



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BiBTeXエントリ 
@article{id544,
         title = {Explanation vs Performance in Data Mining:  A Case Study with Predicting Runaway Projects},
        author = {Tim Menzies and Osamu Mizuno and Yasunari Takagi and Tohru Kikuno},
       journal = {Journal of Software Engineering and Applications},
        volume = {2},
        number = {4},
         pages = {221-236},
         month = {11},
          year = {2009},
}