![](https://blogimg.goo.ne.jp/user_image/55/17/09379d0cf8b3605cc4b23dc5a7d866a2.jpg)
Eric P. Xing, Michael I. Jordan, Richard M. Karp
Feature selection for high-dimensional genomic microarray data
Proceedings of the Eighteenth International Conference on Machine Learning, (ICML2001).
[PDF][Web Site]
・遺伝子抽出法の提案
・データ:ヒト, 白血病(ALL/AML),72サンプル, 7130遺伝子 [Golub.1999]
・遺伝子抽出法:Markov Blanket filter [Koller and Sahami,1996]を改良
・クラス識別法:1.Gaussian classifier, 2.Logistic classifier, 3.Nearest neighbor classifier
・抽出法「Our approach is a hybrid of filter and wrapper approaches to feature selection.」
・「Wrapper algorithms can perform better than filter algorithms, but they can require orders of magnitude more computation time.」
Feature selection for high-dimensional genomic microarray data
Proceedings of the Eighteenth International Conference on Machine Learning, (ICML2001).
[PDF][Web Site]
・遺伝子抽出法の提案
・データ:ヒト, 白血病(ALL/AML),72サンプル, 7130遺伝子 [Golub.1999]
・遺伝子抽出法:Markov Blanket filter [Koller and Sahami,1996]を改良
・クラス識別法:1.Gaussian classifier, 2.Logistic classifier, 3.Nearest neighbor classifier
・抽出法「Our approach is a hybrid of filter and wrapper approaches to feature selection.」
・「Wrapper algorithms can perform better than filter algorithms, but they can require orders of magnitude more computation time.」
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