TY - GEN
T1 - Fuzzy c-means for data with tolerance by introducing penalty term
AU - Kanzawa, Yuchi
AU - Endo, Yasunori
AU - Miyamoto, Sadaaki
PY - 2008/12/1
Y1 - 2008/12/1
N2 - In this paper, two new clustering algorithms are proposed for data with some errors. In any of these algorithms, the error is interpreted as one of decision variables - called "tolerance" - of a certain optimization problem like the previously proposed algorithm, but the tolerance in new methods is determined by the new introduced penalty term of it in the corresponding objective function. Through some numerical experiments, the difference between our methods andthe previously proposed one is discussed.
AB - In this paper, two new clustering algorithms are proposed for data with some errors. In any of these algorithms, the error is interpreted as one of decision variables - called "tolerance" - of a certain optimization problem like the previously proposed algorithm, but the tolerance in new methods is determined by the new introduced penalty term of it in the corresponding objective function. Through some numerical experiments, the difference between our methods andthe previously proposed one is discussed.
UR - http://www.scopus.com/inward/record.url?scp=70349285018&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70349285018&partnerID=8YFLogxK
U2 - 10.1109/SMCIA.2008.5045992
DO - 10.1109/SMCIA.2008.5045992
M3 - Conference contribution
AN - SCOPUS:70349285018
SN - 9781424437825
T3 - SMCia/08 - Proceedings of the 2008 IEEE Conference on Soft Computing on Industrial Applications
SP - 371
EP - 376
BT - SMCia/08 - Proceedings of the 2008 IEEE Conference on Soft Computing on Industrial Applications
T2 - 2008 IEEE Conference on Soft Computing on Industrial Applications, SMCia/08
Y2 - 25 June 2008 through 27 June 2008
ER -