Interval data clustering using self-organizing maps based on adaptive Mahalanobis distances
type: Item
instance of: scholarly article
title: Interval data clustering using self-organizing maps based on adaptive Mahalanobis distances
zbMATH Open document ID: 1296.68129
author: Chantal Hajjar
author: Hani Hamdan
published in: Neural Networks
publication date: 2014-10-10T00:00:00Z
Mathematics Subject Classification ID: 68T05
Mathematics Subject Classification ID: 62H30
zbMATH DE Number: 6353461
zbMATH Keywords: self-organizing maps
zbMATH Keywords: interval data
zbMATH Keywords: Mahalanobis distance
zbMATH Keywords: unsupervised learning
zbMATH Keywords: clustering
Wikidata QID: Q30638269
MaRDI profile type: Publication
full work available at URL: j.neunet.2013.04.009
OpenAlex ID: W2045527658
cites work: 6. Symbolic Data Analysis
cites work: Q4445234
cites work: Dynamic clustering for interval data based on \(L_2\) distance
cites work: Self-organization and associative memory
DOI: 10.1016/J.NEUNET.2013.04.009
description: scientific article; zbMATH DE number 6353461