TY - CHAP
T1 - Symbolic Hierarchical Clustering for Pain Vector
AU - Katayama, Kotoe
AU - Yamaguchi, Rui
AU - Imoto, Seiya
AU - Matsuura, Keiko
AU - Watanabe, Kenji
AU - Miyano, Satoru
PY - 2012
Y1 - 2012
N2 - We propose a hierarchical clustering in the framework of Symbolic Data Analysis(SDA). SDA was proposed by Diday at the end of the 1980s and is a new approach for analysing huge and complex data. In SDA, an observation is described by not only numerical values but also "higher-level units"; sets, intervals, distributions, etc. Most SDA works have dealt with only intervals as the descriptions. We already proposed "pain distribution" as new type data in SDA. In this paper, we define new "pain vector" as new type data in SDA and propose a hierarchical clustering for this new type data.
AB - We propose a hierarchical clustering in the framework of Symbolic Data Analysis(SDA). SDA was proposed by Diday at the end of the 1980s and is a new approach for analysing huge and complex data. In SDA, an observation is described by not only numerical values but also "higher-level units"; sets, intervals, distributions, etc. Most SDA works have dealt with only intervals as the descriptions. We already proposed "pain distribution" as new type data in SDA. In this paper, we define new "pain vector" as new type data in SDA and propose a hierarchical clustering for this new type data.
KW - Distribution-Valued Data
KW - Visual Analogue Scale
UR - http://www.scopus.com/inward/record.url?scp=84879262899&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84879262899&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-29920-9_13
DO - 10.1007/978-3-642-29920-9_13
M3 - Chapter
AN - SCOPUS:84879262899
SN - 9783642299193
T3 - Smart Innovation, Systems and Technologies
SP - 117
EP - 124
BT - Intelligent Decision Technologies Proceedings of the 4th International Conference on Intelligent Decision
A2 - Lakhmi, Jain
A2 - Robert, Howlett
A2 - Junzo, Watada
A2 - Toyohide, Watanabe
A2 - Phillips-Wren, Gloria
ER -