4.6 Article

SOM-ELM Self-Organized Clustering using ELM

Journal

NEUROCOMPUTING
Volume 165, Issue -, Pages 238-254

Publisher

ELSEVIER
DOI: 10.1016/j.neucom.2015.03.014

Keywords

ELM; Self-Organized; SOM; Clustering

Ask authors/readers for more resources

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. (C) 2015 Elsevier B.V. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available