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  Clustering with the Fisher score

Tsuda, K., Kawanabe, M., & Müller, K.-R. (2003). Clustering with the Fisher score. In S. Becker, S. Thrun, & K. Obermayer (Eds.), Advances in Neural Information Processing Systems 15 (pp. 729-736). Cambridge, MA, USA: MIT Press.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-DB39-C Version Permalink: https://hdl.handle.net/21.11116/0000-0005-6BD1-7
Genre: Conference Paper

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http://papers.nips.cc/paper/2292-clustering-with-the-fisher-score.pdf (Publisher version)
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 Creators:
Tsuda, K1, Author           
Kawanabe, M, Author
Müller, K-R1, Author           
Affiliations:
1External Organizations, ou_persistent22              

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 Abstract: Recently the Fisher score (or the Fisher kernel) is increasingly used as a feature extractor for classification problems. The Fisher score is a vector of parameter derivatives of loglikelihood of a probabilistic model. This
paper gives a theoretical analysis about how class information is preserved in the space of the Fisher score, which turns out that the Fisher score consists of a few important dimensions with class information and many nuisance dimensions. When we perform clustering with the Fisher score, K-Means type methods are obviously inappropriate because they make use of all dimensions. So we will develop a novel but simple clustering
algorithm specialized for the Fisher score, which can exploit important dimensions. This algorithm is successfully tested in experiments with artificial data and real data (amino acid sequences).

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 Dates: 2003-09
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 2175
 Degree: -

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Title: Sixteenth Annual Conference on Neural Information Processing Systems (NIPS 2002)
Place of Event: Vancouver, BC, Canada
Start-/End Date: 2002-12-09 - 2002-12-14

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Title: Advances in Neural Information Processing Systems 15
Source Genre: Proceedings
 Creator(s):
Becker, S, Editor
Thrun, S, Editor
Obermayer, K, Editor
Affiliations:
-
Publ. Info: Cambridge, MA, USA : MIT Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 729 - 736 Identifier: ISBN: 0-262-02550-7