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  Multi-Classification by Categorical Features via Clustering

Seldin, Y., & Tishby, N. (2008). Multi-Classification by Categorical Features via Clustering. In W. Cohen, A. McCallum, & S. Roweis (Eds.), ICML '08: Proceedings of the 25th international conference on Machine (pp. 920-927). New York, NY, USA: ACM Press.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-C8FF-7 Version Permalink: https://hdl.handle.net/21.11116/0000-0003-A7C3-4
Genre: Conference Paper

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https://dl.acm.org/citation.cfm?doid=1390156.1390272 (Publisher version)
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 Creators:
Seldin, Y1, Author           
Tishby, N, Author
Affiliations:
1External Organizations, ou_persistent22              

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 Abstract: We derive a generalization bound for multi-classification schemes based on grid clustering in categorical parameter product spaces. Grid clustering partitions the parameter space in the form of a Cartesian product of partitions for each of the parameters. The derived bound provides a means to evaluate clustering solutions in terms of the generalization power of a built-on classifier. For classification based on a single feature the bound serves to find a globally optimal classification rule. Comparison of the generalization power of individual features can then be used for feature ranking. Our experiments show that in this role the bound is much more precise than mutual information or normalized correlation indices.

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 Dates: 2008-07
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 6575
DOI: 10.1145/1390156.1390272
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Title: 25th International Conference on Machine Learning (ICML 2008)
Place of Event: Helsinki, Finland
Start-/End Date: 2008-06-05 - 2008-06-09

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Title: ICML '08: Proceedings of the 25th international conference on Machine
Source Genre: Proceedings
 Creator(s):
Cohen, WW, Editor
McCallum, A, Editor
Roweis, ST, Editor
Affiliations:
-
Publ. Info: New York, NY, USA : ACM Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 920 - 927 Identifier: ISBN: 978-1-60558-205-4