Learning to improve area-under-FROC for imbalanced medical data classification using an ensemble method

doi:10.1145/1540276.1540290

Learning to improve area-under-FROC for imbalanced medical data classification using an ensemble method

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Authors:	Hung-Yi Lo	National Taiwan University, Taipei, Taiwan
	Chun-Min Chang	National Taiwan University, Taipei, Taiwan
	Tsung-Hsien Chiang	National Taiwan University, Taipei, Taiwan
	Cho-Yi Hsiao	National Taiwan University, Taipei, Taiwan
	Anta Huang	National Taiwan University, Taipei, Taiwan
	Tsung-Ting Kuo	National Taiwan University, Taipei, Taiwan
	Wei-Chi Lai	National Taiwan University, Taipei, Taiwan
	Ming-Han Yang	National Taiwan University, Taipei, Taiwan
	Jung-Jung Yeh	National Taiwan University, Taipei, Taiwan
	Chun-Chao Yen	National Taiwan University, Taipei, Taiwan
	Shou-De Lin	National Taiwan University, Taipei, Taiwan

	2008 Article Review
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	ACM SIGKDD Explorations Newsletter archive
	Volume 10 Issue 2, December 2008 Pages 43-46 ACM New York, NY, USA table of contents doi>10.1145/1540276.1540290

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Tags: adaboost area under free response receiver operating curves breast cancer image classification classifier design and evaluation data mining design ensemble method experimentation measurement medical information systems performance support vector machines

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