Memberships Networks for High-Dimensional Fuzzy Clustering Visualization

Leandro Ariza-Jiménez, Luisa F. Villa, Olga Lucía Quintero

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Visualizing the cluster structure of high-dimensional data is a non-trivial task that must be able to deal with the large dimensionality of the input data. Unlike hard clustering structures, visualization of fuzzy clusterings is not as straightforward because soft clustering algorithms yield more complex clustering structures. Here is introduced the concept of membership networks, an undirected weighted network constructed based on the fuzzy partition matrix that represents a fuzzy clustering. This simple network-based method allows understanding visually how elements involved in this kind of complex data clustering structures interact with each other, without relying on a visualization of the input data themselves. Experiment results demonstrated the usefulness of the proposed method for the exploration and analysis of clustering structures on the Iris flower data set and two large and unlabeled financial datasets, which describes the financial profile of customers of a local bank.

Original languageEnglish
Title of host publicationApplied Computer Sciences in Engineering - 6th Workshop on Engineering Applications, WEA 2019, Proceedings
EditorsJuan Carlos Figueroa-García, Mario Duarte-González, Sebastián Jaramillo-Isaza, Alvaro David Orjuela-Cañon, Yesid Díaz-Gutierrez
PublisherSpringer Heidelberg
Pages263-273
Number of pages11
ISBN (Print)9783030310189
DOIs
StatePublished - 1 Jan 2019
Event6th Workshop on Engineering Applications, WEA 2019 - Santa Marta, Colombia
Duration: 16 Oct 201918 Oct 2019

Publication series

NameCommunications in Computer and Information Science
Volume1052
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference6th Workshop on Engineering Applications, WEA 2019
Country/TerritoryColombia
CitySanta Marta
Period16/10/1918/10/19

Keywords

  • Clustering visualization
  • Fuzzy clustering
  • High-dimensional data
  • Membership network

Product types of Minciencias

  • B article - Q3

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