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The clustering problem consists in the discovery of interesting groups in a data set. Such task is very important and widely tacked in the literature. The K-means algorithm is one of the most popular techniques in clustering. However, the performance of the K-means algorithm depends highly on initial cluster centers and converges to local minima. This paper proposed a simple water cycle algorithm...
Clustering is a popular data analysis and data mining technique. The k-means clustering algorithm is one of the most commonly used methods. However, it highly depends on the initial solution and is easy to trap into the local optimal. For overcoming these disadvantages of the k-means method, Flower Pollination Algorithm with Bee Pollinator is proposed. Discard pollen operator and crossover operator...
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