EM algorithm for GTM-FS


We propose a generative topographic mapping (GTM) based data visualization with simultaneous feature selection (GTM-FS) approach which not only provides a better visualization by modeling irrelevant features ("noise") using a separate shared distribution but also gives a saliency value for each feature which helps the user to assess their significance. This technical report presents a varient of the Expectation-Maximization (EM) algorithm for GTM-FS.

Divisions: ?? 50811700Jl ??
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
Uncontrolled Keywords: generative topographic mapping,data visualization,simultaneous feature selection,Expectation-Maximization algorithm,GTM-FS
ISBN: NCRG/2005/012
Last Modified: 11 Jan 2024 08:24
Date Deposited: 11 Mar 2019 17:22
PURE Output Type: Technical report
Published Date: 2005-11-02
Authors: Maniyar, Dharmesh M.
Nabney, Ian T. (ORCID Profile 0000-0003-1513-993X)

Export / Share Citation


Additional statistics for this record