Genetic Weighted K-means for Large-Scale Clustering Problems.
Fang‐Xiang Wu, ANTHONY J. KUSALIK, Wenjun Zhang · 2005
This paper proposes a genetic weighted K-means algorithm called GWKMA, which is a hybridization of a genetic algorithm (GA) and a weighted K-means algorithm (WKMA). GWKMA encodes each individual by a partitioning table which uniquely determines a clustering, and employs three genetic operators (selection, crossover, mutation) and a WKMA operator. The superiority of the GWKMA over the WKMA and other GA-clustering algorithms without the WKMA operator is demonstrated. 1.