TY - GEN
T1 - On Some Fuzzy Clustering Algorithms with Dimensionality Reduction
AU - Kawamura, Masanori
AU - Kanzawa, Yuchi
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Certain fuzzy clustering algorithms involve dimensionality reduction techniques, such as principal component analysis (PCA), probabilistic principal component analysis (PPCA), and t-factor analysis (t-FA). Other fuzzification techniques have been applied to fuzzy clustering without dimensionality reduction. In this study, eleven fuzzy clustering algorithms are proposed based on five dimensionality reduction methods: PCA, PPCA, t-distribution-based PPCA, FA, and t-FA; and three fuzzification techniques: Bezdek-type, Kullback-Leibler divergence-regularization, and q-divergence-regularization. Based on numerical experiments using an artificial dataset, it is shown that some of the proposed methods outperforms the conventional methods on clustering accuracy.
AB - Certain fuzzy clustering algorithms involve dimensionality reduction techniques, such as principal component analysis (PCA), probabilistic principal component analysis (PPCA), and t-factor analysis (t-FA). Other fuzzification techniques have been applied to fuzzy clustering without dimensionality reduction. In this study, eleven fuzzy clustering algorithms are proposed based on five dimensionality reduction methods: PCA, PPCA, t-distribution-based PPCA, FA, and t-FA; and three fuzzification techniques: Bezdek-type, Kullback-Leibler divergence-regularization, and q-divergence-regularization. Based on numerical experiments using an artificial dataset, it is shown that some of the proposed methods outperforms the conventional methods on clustering accuracy.
KW - Factor Analysis
KW - Fuzzy Clustering
KW - Probabilistic Principal Component Analysis
KW - t-distribution
UR - http://www.scopus.com/inward/record.url?scp=85146672083&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85146672083&partnerID=8YFLogxK
U2 - 10.1109/SCISISIS55246.2022.10001956
DO - 10.1109/SCISISIS55246.2022.10001956
M3 - Conference contribution
AN - SCOPUS:85146672083
T3 - 2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2022
BT - 2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2022
Y2 - 29 November 2022 through 2 December 2022
ER -