loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Na Li ; Nicolas Lefebvre and Régis Lengellé

Affiliation: Université de Technologie de Troyes, France

Keyword(s): Hierarchical Agglomerative Clustering, Gap Statistics, Kernel Alignment, Number of Clusters.

Related Ontology Subjects/Areas/Topics: Clustering ; Kernel Methods ; Pattern Recognition ; Theory and Methods

Abstract: Clustering algorithms, as unsupervised analysis tools, are useful for exploring data structure and have owned great success in many disciplines. For most of the clustering algorithms like k-means, determining the number of the clusters is a crucial step and is one of the most difficult problems. Hierarchical Agglomerative Clustering (HAC) has the advantage of giving a data representation by the dendrogram that allows clustering by cutting the dendrogram at some optimal level. In the past years and within the context of HAC, efficient statistics have been proposed to estimate the number of clusters and the Gap Statistic by Tibshirani has shown interesting performances. In this paper, we propose some new Gap Statistics to further improve the determination of the number of clusters. Our works focus on the kernelized version of the widely-used Hierarchical Clustering Algorithm.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.149.251.154

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Li, N.; Lefebvre, N. and Lengellé, R. (2014). Kernel Hierarchical Agglomerative Clustering - Comparison of Different Gap Statistics to Estimate the Number of Clusters. In Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-018-5; ISSN 2184-4313, SciTePress, pages 255-262. DOI: 10.5220/0004828202550262

@conference{icpram14,
author={Na Li. and Nicolas Lefebvre. and Régis Lengellé.},
title={Kernel Hierarchical Agglomerative Clustering - Comparison of Different Gap Statistics to Estimate the Number of Clusters},
booktitle={Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2014},
pages={255-262},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004828202550262},
isbn={978-989-758-018-5},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Kernel Hierarchical Agglomerative Clustering - Comparison of Different Gap Statistics to Estimate the Number of Clusters
SN - 978-989-758-018-5
IS - 2184-4313
AU - Li, N.
AU - Lefebvre, N.
AU - Lengellé, R.
PY - 2014
SP - 255
EP - 262
DO - 10.5220/0004828202550262
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic