GRASP IN THE RESOLUTION OF THE CLUSTERING PROBLEM
DOI:
https://doi.org/10.15381/risi.v2i2.3110Keywords:
Grasp, K-Means, Clustering, Classification, Meta Heuristic.Abstract
The clustering could be approached as a combinatorial optimization problem when the clusters are a partition of an objects set. The Grasp meta-heuristic is a relatively recent technic that had been used to solve of an e_cient manner several combinatorial optimization problems. In this work, we adapted the Grasp metaheuristic to solve the clustering problem based on the basis of K-Means algorithm. The proposed algorithm, named GraspKM, takes advantages of fast convergence of K-Means algorithm avoiding the inconvenience of obtaining a local optimal. The algorithm shows to be better than KMeans algorithm and it is comparable with another meta-heuristic method reviewed with respect to e_ciency. The computational experiments had been realized with a data collection extensively used on clustering literature.Downloads
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Copyright (c) 2005 Erick Vicente, Luis Rivera, David Mauricio
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