Article
Non-metric conceptual clustering : a new tool for investigating urban quality of life (1)
Cybergeo: European Journal of Geography
(1999)
Abstract
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.
Keywords
- non metric conceptual clustering,
- factor analysis,
- quality of life
Disciplines
Publication Date
October 6, 1999
DOI
10.4000/cybergeo.4963
Citation Information
Patrick H. Buckley and Debnath Mookherjee. "Non-metric conceptual clustering : a new tool for investigating urban quality of life (1)" Cybergeo: European Journal of Geography (1999) Available at: http://works.bepress.com/patrick-buckley/10/