Subspace clustering based on compressibility

Masaki Narahashi, Einoshin Suzuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, we propose a subspace clustering method based on compressibility. It is widely accepted that compressibility is deeply related to inductive learning. We have come to believe that compressibility is promising as an evaluation criterion in subspace clustering, and propose SUBCCOM in order to verify this belief. Experimental evaluation employs both artificial and real data sets.

Original languageEnglish
Title of host publicationDiscovery Science - 5th International Conference, DS 2002, Proceedings
EditorsCarl H. Smith, Steffen Lange, Ken Satoh
PublisherSpringer Verlag
Pages435-440
Number of pages6
ISBN (Print)3540001883, 9783540001881
Publication statusPublished - Jan 1 2002
Externally publishedYes
Event5th International Conference on Discovery Science, DS 2002 - Lubeck, Germany
Duration: Nov 24 2002Nov 26 2002

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2534
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other5th International Conference on Discovery Science, DS 2002
CountryGermany
CityLubeck
Period11/24/0211/26/02

Fingerprint

Subspace Clustering
Compressibility
Inductive Learning
Subspace Methods
Clustering Methods
Experimental Evaluation
Verify
Evaluation

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Narahashi, M., & Suzuki, E. (2002). Subspace clustering based on compressibility. In C. H. Smith, S. Lange, & K. Satoh (Eds.), Discovery Science - 5th International Conference, DS 2002, Proceedings (pp. 435-440). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2534). Springer Verlag.

Subspace clustering based on compressibility. / Narahashi, Masaki; Suzuki, Einoshin.

Discovery Science - 5th International Conference, DS 2002, Proceedings. ed. / Carl H. Smith; Steffen Lange; Ken Satoh. Springer Verlag, 2002. p. 435-440 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2534).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Narahashi, M & Suzuki, E 2002, Subspace clustering based on compressibility. in CH Smith, S Lange & K Satoh (eds), Discovery Science - 5th International Conference, DS 2002, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2534, Springer Verlag, pp. 435-440, 5th International Conference on Discovery Science, DS 2002, Lubeck, Germany, 11/24/02.
Narahashi M, Suzuki E. Subspace clustering based on compressibility. In Smith CH, Lange S, Satoh K, editors, Discovery Science - 5th International Conference, DS 2002, Proceedings. Springer Verlag. 2002. p. 435-440. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Narahashi, Masaki ; Suzuki, Einoshin. / Subspace clustering based on compressibility. Discovery Science - 5th International Conference, DS 2002, Proceedings. editor / Carl H. Smith ; Steffen Lange ; Ken Satoh. Springer Verlag, 2002. pp. 435-440 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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