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Activity Number:
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166
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Type:
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Invited
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Date/Time:
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Monday, August 4, 2008 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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| Abstract - #300155 |
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Title:
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Large Margin Hierarchical Classification
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Author(s):
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Huxiang Wang and Xiaotong Shen*+ and Wei Pan
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Companies:
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The University of Minnesota and The University of Minnesota and The University of Minnesota
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Address:
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School of Statistics, Minneapolis, MN, 55455,
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Keywords:
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Abstract:
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In this talk, we will present a large margin method for hierarchical classification. The main focus here is to utilize the inter-class dependency to improve the classification performance of flat classification. In such a situation, flat classification is infeasible in the presence of a large number of classes, which occurs often in gene function discovery. Various hierarchical losses will be discussed, in addition to some numerical examples in gene function prediction.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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