TY - JOUR
T1 - Fuzzy c-means algorithms for data with tolerance based on opposite criterions
AU - Yuchi, Kanzawa
AU - Yasunori, Endo
AU - Sadaaki, Miyamoto
PY - 2007/10
Y1 - 2007/10
N2 - In this paper, two new clustering algorithms are proposed for the 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 is determined based on the opposite criterion to its corresponding previously proposed one. Applying our each algorithm together with its corresponding previously proposed one, a reliability of the clustering result is discussed. Through some numerical experiments, the validity of this paper is discussed.
AB - In this paper, two new clustering algorithms are proposed for the 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 is determined based on the opposite criterion to its corresponding previously proposed one. Applying our each algorithm together with its corresponding previously proposed one, a reliability of the clustering result is discussed. Through some numerical experiments, the validity of this paper is discussed.
KW - Clustering
KW - Fuzzy c-means
KW - Reliability of the clustering result
KW - Tolerance
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U2 - 10.1093/ietfec/e90-a.10.2194
DO - 10.1093/ietfec/e90-a.10.2194
M3 - Article
AN - SCOPUS:68249138529
SN - 0916-8508
VL - E90-A
SP - 2194
EP - 2202
JO - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
JF - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
IS - 10
ER -