Non-metric conceptual clustering: a new tool for investigating urban quality of life (1)

Based on the use of a non-metric conceptual clustering technique, this empirical study explores the quality of life of a small metropolitan city. The RIFFLE program, developed at Western Washington University, is utilized to explicitly address the clustering algorithm where a subset n of m variables...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Patrick H. Buckley, Debnath Mookherjee
Formato:	article
Lenguaje:	DE EN FR IT PT
Publicado:	Unité Mixte de Recherche 8504 Géographie-cités 1999
Materias:	non metric conceptual clustering factor analysis quality of life Geography (General) G1-922
Acceso en línea:	https://doaj.org/article/ac0b6789747d43e5911bf6914d6660c2
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:ac0b6789747d43e5911bf6914d6660c2
record_format	dspace
spelling	oai:doaj.org-article:ac0b6789747d43e5911bf6914d6660c22021-12-02T11:10:22ZNon-metric conceptual clustering: a new tool for investigating urban quality of life (1)1278-336610.4000/cybergeo.4963https://doaj.org/article/ac0b6789747d43e5911bf6914d6660c21999-10-01T00:00:00Zhttp://journals.openedition.org/cybergeo/4963https://doaj.org/toc/1278-3366Based on the use of a non-metric conceptual clustering technique, this empirical study explores the quality of life of a small metropolitan city. The RIFFLE program, developed at Western Washington University, is utilized to explicitly address the clustering algorithm where a subset n of m variables creates an n dimension vector space partitioned into two or more clusters in each dimension. Applying a variation of Guttman's Lambda n variables and c clusters are reported by RIFFLE that predict the pattern. Non-metric conceptual clustering overcomes a number of problems common in traditional techniques such as data assumptions, relevancy and missing data.Patrick H. BuckleyDebnath MookherjeeUnité Mixte de Recherche 8504 Géographie-citésarticlenon metric conceptual clusteringfactor analysisquality of lifeGeography (General)G1-922DEENFRITPTCybergeo (1999)
institution	DOAJ
collection	DOAJ
language	DE EN FR IT PT
topic	non metric conceptual clustering factor analysis quality of life Geography (General) G1-922
spellingShingle	non metric conceptual clustering factor analysis quality of life Geography (General) G1-922 Patrick H. Buckley Debnath Mookherjee Non-metric conceptual clustering: a new tool for investigating urban quality of life (1)
description	Based on the use of a non-metric conceptual clustering technique, this empirical study explores the quality of life of a small metropolitan city. The RIFFLE program, developed at Western Washington University, is utilized to explicitly address the clustering algorithm where a subset n of m variables creates an n dimension vector space partitioned into two or more clusters in each dimension. Applying a variation of Guttman's Lambda n variables and c clusters are reported by RIFFLE that predict the pattern. Non-metric conceptual clustering overcomes a number of problems common in traditional techniques such as data assumptions, relevancy and missing data.
format	article
author	Patrick H. Buckley Debnath Mookherjee
author_facet	Patrick H. Buckley Debnath Mookherjee
author_sort	Patrick H. Buckley
title	Non-metric conceptual clustering: a new tool for investigating urban quality of life (1)
title_short	Non-metric conceptual clustering: a new tool for investigating urban quality of life (1)
title_full	Non-metric conceptual clustering: a new tool for investigating urban quality of life (1)
title_fullStr	Non-metric conceptual clustering: a new tool for investigating urban quality of life (1)
title_full_unstemmed	Non-metric conceptual clustering: a new tool for investigating urban quality of life (1)
title_sort	non-metric conceptual clustering: a new tool for investigating urban quality of life (1)
publisher	Unité Mixte de Recherche 8504 Géographie-cités
publishDate	1999
url	https://doaj.org/article/ac0b6789747d43e5911bf6914d6660c2
work_keys_str_mv	AT patrickhbuckley nonmetricconceptualclusteringanewtoolforinvestigatingurbanqualityoflife1 AT debnathmookherjee nonmetricconceptualclusteringanewtoolforinvestigatingurbanqualityoflife1
_version_	1718396179685834752

Non-metric conceptual clustering: a new tool for investigating urban quality of life (1)

Ejemplares similares