TY - GEN
T1 - A genetic algorithm implementation of the fuzzy least trimmed squares clustering
AU - Banerjee, Amit
AU - Louis, Sushil J.
PY - 2007/12/1
Y1 - 2007/12/1
N2 - This paper describes a new approach to finding a global solution for the fuzzy least trimmed squares clustering. The least trimmed squares (LTS) estimator is known to be a high breakdown estimator, in both regression and clustering. From the point of view of implementation, the feasible solution algorithm is one of the few known techniques that guarantees a global solution for the LTS estimator. The feasible solution algorithm divides a noisy data set into two parts - the non-noisy retained set and the noisy trimmed set, by implementing a pairwise swap of datum between the two sets until a least squares estimator provides the best fit on the retained set. We present a novel genetic algorithm-based implementation of the feasible solution algorithm for fuzzy least trimmed squares clustering, and also substantiate the efficacy of our method by three examples.
AB - This paper describes a new approach to finding a global solution for the fuzzy least trimmed squares clustering. The least trimmed squares (LTS) estimator is known to be a high breakdown estimator, in both regression and clustering. From the point of view of implementation, the feasible solution algorithm is one of the few known techniques that guarantees a global solution for the LTS estimator. The feasible solution algorithm divides a noisy data set into two parts - the non-noisy retained set and the noisy trimmed set, by implementing a pairwise swap of datum between the two sets until a least squares estimator provides the best fit on the retained set. We present a novel genetic algorithm-based implementation of the feasible solution algorithm for fuzzy least trimmed squares clustering, and also substantiate the efficacy of our method by three examples.
UR - http://www.scopus.com/inward/record.url?scp=50249118387&partnerID=8YFLogxK
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U2 - 10.1109/FUZZY.2007.4295399
DO - 10.1109/FUZZY.2007.4295399
M3 - Conference contribution
AN - SCOPUS:50249118387
SN - 1424412102
SN - 9781424412105
T3 - IEEE International Conference on Fuzzy Systems
BT - 2007 IEEE International Conference on Fuzzy Systems, FUZZY
T2 - 2007 IEEE International Conference on Fuzzy Systems, FUZZY
Y2 - 23 July 2007 through 26 July 2007
ER -