TY - JOUR
T1 - Regularized fuzzy c-means clustering and its behavior at point of infinity
AU - Kanzawa, Yuchi
AU - Miyamoto, Sadaaki
N1 - Publisher Copyright:
© 2019 Fuji Technology Press. All rights reserved.
PY - 2019/5
Y1 - 2019/5
N2 - This study shows that a general regularized fuzzy cmeans (rFCM) clustering algorithm, including some conventional clustering algorithms, can be constructed if a given regularizer function value, its derivative function value, and its inverse derivative function value can be calculated. Furthermore, the results of the study show that the behavior of the fuzzy classification function for rFCM at an infinity point is similar to that for some conventional clustering algorithms.
AB - This study shows that a general regularized fuzzy cmeans (rFCM) clustering algorithm, including some conventional clustering algorithms, can be constructed if a given regularizer function value, its derivative function value, and its inverse derivative function value can be calculated. Furthermore, the results of the study show that the behavior of the fuzzy classification function for rFCM at an infinity point is similar to that for some conventional clustering algorithms.
KW - Fuzzy clustering
KW - regularization
UR - http://www.scopus.com/inward/record.url?scp=85067982523&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85067982523&partnerID=8YFLogxK
U2 - 10.20965/jaciii.2019.p0485
DO - 10.20965/jaciii.2019.p0485
M3 - Article
AN - SCOPUS:85067982523
SN - 1343-0130
VL - 23
SP - 485
EP - 492
JO - Journal of Advanced Computational Intelligence and Intelligent Informatics
JF - Journal of Advanced Computational Intelligence and Intelligent Informatics
IS - 3
ER -