Automatic Clustering Using a Synergy of Genetic Algorithm and Multi-objective Differential Evolution

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Provided by: Jadavpur University
Topic: Big Data
Format: PDF
In this paper, the authors apply the Differential Evolution (DE) and Genetic Algorithm (GA) to the task of automatic fuzzy clustering in a Multi-objective Optimization (MO) framework. It compares the performance a hybrid of the GA and DE (GADE) algorithms over the fuzzy clustering problem, where two conflicting fuzzy validity indices are simultaneously optimized. The resultant Pareto optimal set of solutions from each algorithm consists of a number of non-dominated solutions, from which the user can choose the most promising ones according to the problem specifications.
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