A Novel Multiobjective K-harmonic Means Clustering Algorithm using Levy Flight Cuckoo Search

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Provided by: Binary Information Press
Topic: Data Management
Format: PDF
K-Harmonic Means (KHM) is a centroid based clustering algorithm, which will easily converge to local optimal and optimize single objective function. Recent researches have shown that there is no single cluster validity index works equally well for different kinds of datasets. Multi-objective clustering is used to solve this problem, which optimizes multiple validity measures simultaneously. Besides Levy flight Cuckoo Search is a recent developed nature inspired meta-heuristic algorithm that works efficiently for clustering. These facts motivate the users' to propose a novel Multi-Objective KHM clustering algorithm using Levy Flight Cuckoo Search (MOKHMCS) which optimizes the KHM objective function and Xie-Beni index simultaneously.
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