Evaluation of topographic clustering and its kernelization

Marie Jeanne Lesot; Florence D'Alché-Buc; Georges Siolas

doi:10.1007/978-3-540-39857-8_25

Evaluation of topographic clustering and its kernelization

Marie Jeanne Lesot
, Florence D'Alché-Buc
, Georges Siolas

LIP6, UPMC Sorbonne Universités - Paris 6

Research output: Contribution to journal › Conference article › peer-review

Abstract

We consider the topographic clustering task and focus on the problem of its evaluation, which enables to perform model selection: topographic clustering algorithms, from the original Self Organizing Map to its extension based on kernel (STMK), can be viewed in the unified framework of constrained clustering. Exploiting this point of view, we discuss existing quality measures and we propose a new criterion based on an F-measure, which combines a compacity with an organization criteria and extend it to their kernel-based version.

Original language	English
Pages (from-to)	265-276
Number of pages	12
Journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2837
DOIs	https://doi.org/10.1007/978-3-540-39857-8_25
Publication status	Published - 1 Jan 2003
Externally published	Yes
Event	14th European Conference on Machine Learning - Cavtat-Dubrovnik, Croatia Duration: 22 Sept 2003 → 26 Sept 2003

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10.1007/978-3-540-39857-8_25

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title = "Evaluation of topographic clustering and its kernelization",

abstract = "We consider the topographic clustering task and focus on the problem of its evaluation, which enables to perform model selection: topographic clustering algorithms, from the original Self Organizing Map to its extension based on kernel (STMK), can be viewed in the unified framework of constrained clustering. Exploiting this point of view, we discuss existing quality measures and we propose a new criterion based on an F-measure, which combines a compacity with an organization criteria and extend it to their kernel-based version.",

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Evaluation of topographic clustering and its kernelization. / Lesot, Marie Jeanne; D'Alché-Buc, Florence; Siolas, Georges.
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 2837, 01.01.2003, p. 265-276.

Research output: Contribution to journal › Conference article › peer-review

TY - JOUR

T1 - Evaluation of topographic clustering and its kernelization

AU - Lesot, Marie Jeanne

AU - D'Alché-Buc, Florence

AU - Siolas, Georges

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N2 - We consider the topographic clustering task and focus on the problem of its evaluation, which enables to perform model selection: topographic clustering algorithms, from the original Self Organizing Map to its extension based on kernel (STMK), can be viewed in the unified framework of constrained clustering. Exploiting this point of view, we discuss existing quality measures and we propose a new criterion based on an F-measure, which combines a compacity with an organization criteria and extend it to their kernel-based version.

AB - We consider the topographic clustering task and focus on the problem of its evaluation, which enables to perform model selection: topographic clustering algorithms, from the original Self Organizing Map to its extension based on kernel (STMK), can be viewed in the unified framework of constrained clustering. Exploiting this point of view, we discuss existing quality measures and we propose a new criterion based on an F-measure, which combines a compacity with an organization criteria and extend it to their kernel-based version.

U2 - 10.1007/978-3-540-39857-8_25

DO - 10.1007/978-3-540-39857-8_25

M3 - Conference article

AN - SCOPUS:9444257009

SN - 0302-9743

VL - 2837

SP - 265

EP - 276

JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

T2 - 14th European Conference on Machine Learning

Y2 - 22 September 2003 through 26 September 2003

ER -

Evaluation of topographic clustering and its kernelization

Abstract

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