TY - GEN
T1 - On possibilistic clustering methods based on Shannon/Tsallis-entropy for spherical data and categorical multivariate data
AU - Kanzawa, Yuchi
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - In this paper, four possibilistic clustering methods are proposed. First, we propose two possibilistic clustering methods for spherical data — one based on Shannon entropy, and the other on Tsallis entropy. These methods are derived by subtracting the cosine correlation between an object and a cluster center from 1, to obtain the object-cluster dissimilarity. These methods are derived from the proposed spherical data methods by considering analogies between the spherical and categorical multivariate fuzzy clustering methods, in which the fuzzy methods’ object-cluster similarity calculation is modified to accommodate the proposed possibilistic methods. The validity of the proposed methods is verified through numerical examples.
AB - In this paper, four possibilistic clustering methods are proposed. First, we propose two possibilistic clustering methods for spherical data — one based on Shannon entropy, and the other on Tsallis entropy. These methods are derived by subtracting the cosine correlation between an object and a cluster center from 1, to obtain the object-cluster dissimilarity. These methods are derived from the proposed spherical data methods by considering analogies between the spherical and categorical multivariate fuzzy clustering methods, in which the fuzzy methods’ object-cluster similarity calculation is modified to accommodate the proposed possibilistic methods. The validity of the proposed methods is verified through numerical examples.
KW - Categorical multivariate data
KW - Possibilistic clustering
KW - Spherical data
UR - http://www.scopus.com/inward/record.url?scp=84945573321&partnerID=8YFLogxK
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U2 - 10.1007/978-3-319-23240-9_10
DO - 10.1007/978-3-319-23240-9_10
M3 - Conference contribution
AN - SCOPUS:84945573321
SN - 9783319232393
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 115
EP - 128
BT - Modeling Decisions for Artificial Intelligence - 12th International Conference, MDAI 2015, Proceedings
A2 - Torra, Vicenç
A2 - Narukawa, Yasuo
PB - Springer Verlag
T2 - 12th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2015
Y2 - 21 September 2015 through 23 September 2015
ER -