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SOM-ELM—Self-Organized Clustering using ELM

Authors :
Amaury Lendasse
Anton Akusok
Maite Termenon
Kaj-Mikael Björk
David Veganzones
Eric Séverin
Yoan Miche
Philippe du Jardin
Source :
Neurocomputing. 165:238-254
Publication Year :
2015
Publisher :
Elsevier BV, 2015.

Abstract

This paper presents two new clustering techniques based on Extreme Learning Machine (ELM). These clustering techniques can incorporate a priori knowledge (of an expert) to define the optimal structure for the clusters, i.e. the number of points in each cluster. Using ELM, the first proposed clustering problem formulation can be rewritten as a Traveling Salesman Problem and solved by a heuristic optimization method. The second proposed clustering problem formulation includes both a priori knowledge and a self-organization based on a predefined map (or string). The clustering methods are successfully tested on 5 toy examples and 2 real datasets.

Details

ISSN :
09252312
Volume :
165
Database :
OpenAIRE
Journal :
Neurocomputing
Accession number :
edsair.doi.dedup.....61c056a3b1740f063a1eda5b7f1b8d3b
Full Text :
https://doi.org/10.1016/j.neucom.2015.03.014