TY - JOUR
T1 - Clustering for visual analogue scale data in symbolic data analysis
AU - Katayama, Kotoe
AU - Rui, Yamaguchi
AU - Imoto, Seiya
AU - Matsuura, Keiko
AU - Watanabe, Kenji
AU - Miyano, Satoru
N1 - Funding Information:
This study was partially supported by Health and Labour Sciences Research Grants for Clinical Research from the Ministry of Health, Labour, and Welfare of Japan.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2011
Y1 - 2011
N2 - We propose a hierarchical clustering for the visual analogue scale (VAS) in the framework of Symbolic Data Analysis(SDA). The VAS is a method that can be readily understood by most people to measure a characteristic or attitude that cannot be directly measured. VAS is of most value when looking at change within people, and is of less value for comparing across a group of people because they have different sense. It could be argued that a VAS is trying to produce interval/ratio data out of subjective values that are at best ordinal. Thus, some caution is required in handling VAS. We describe VAS as distribution and handle it as new type data in SDA. In this paper, we define "VAS distribution" as new type data in SDA and propose a hierarchical clustering for this new type data.
AB - We propose a hierarchical clustering for the visual analogue scale (VAS) in the framework of Symbolic Data Analysis(SDA). The VAS is a method that can be readily understood by most people to measure a characteristic or attitude that cannot be directly measured. VAS is of most value when looking at change within people, and is of less value for comparing across a group of people because they have different sense. It could be argued that a VAS is trying to produce interval/ratio data out of subjective values that are at best ordinal. Thus, some caution is required in handling VAS. We describe VAS as distribution and handle it as new type data in SDA. In this paper, we define "VAS distribution" as new type data in SDA and propose a hierarchical clustering for this new type data.
KW - Distribution valued data
KW - Hierarchical clustering
UR - http://www.scopus.com/inward/record.url?scp=84856436272&partnerID=8YFLogxK
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U2 - 10.1016/j.procs.2011.08.068
DO - 10.1016/j.procs.2011.08.068
M3 - Conference article
AN - SCOPUS:84856436272
SN - 1877-0509
VL - 6
SP - 370
EP - 374
JO - Procedia Computer Science
JF - Procedia Computer Science
T2 - Complex Adaptive Systems
Y2 - 30 October 2011 through 2 November 2011
ER -