ELM-SOM+: A continuous mapping for visualization

Published: 01 Jan 2019, Last Modified: 11 Apr 2025Neurocomputing 2019EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: This paper presents a novel dimensionality reduction technique based on ELM and SOM: ELM-SOM+. This technique preserves the intrinsic quality of Self-Organizing Map (SOM): it is nonlinear and suitable for big data. It also brings continuity to the projection using two Extreme Learning Machine (ELM) models, the first one to perform the dimensionality reduction and the second one to perform the reconstruction. ELM-SOM+ is tested successfully on nine diverse datasets. Regarding reconstruction error, the new methodology shows considerable improvement over SOM and brings continuity.
Loading

OpenReview is a long-term project to advance science through improved peer review with legal nonprofit status. We gratefully acknowledge the support of the OpenReview Sponsors. © 2025 OpenReview