Multiple factor analysis and clustering of a mixture of quantitative, categorical and frequency data
type: Item
instance of: scholarly article
title: Multiple factor analysis and clustering of a mixture of quantitative, categorical and frequency data
zbMATH Open document ID: 1452.62406
author: Mónica Bécue-Bertaut
author: Jérôme Pagès
published in: Computational Statistics and Data Analysis
publication date: 2009-06-12T00:00:00Z
Mathematics Subject Classification ID: 62H25
Mathematics Subject Classification ID: 62H30
Mathematics Subject Classification ID: 62-08
zbMATH DE Number: 5564701
zbMATH Keywords: mixed data
zbMATH Keywords: textual data
zbMATH Keywords: distance
zbMATH Keywords: multiple factor analysis
zbMATH Keywords: multiple factor analysis for contingency tables
zbMATH Keywords: clustering
zbMATH Keywords: survey
describes a project that uses: CLUES
describes a project that uses: AFMULT
MaRDI profile type: Publication
full work available at URL: j.csda.2007.09.023
OpenAlex ID: W1973778234
cites work: A principal axes method for comparing contingency tables: MFACT
cites work: Q3339926
cites work: Q4952728
cites work: Effect of using principal coordinates and principal components on retrieval of clusters
cites work: Q3327494
cites work: Multiple factor analysis (AFMULT package)
cites work: Q4355435
cites work: Q3156696
cites work: Q5481434
cites work: CLUES: a non-parametric clustering method based on local shrinking
DOI: 10.1016/J.CSDA.2007.09.023
description: scientific article; zbMATH DE number 5564701