FISHER DISTANCE BASED GA CLUSTERING TAKING INTO ACCOUNT OVERLAPPED SPACE AMONG PROBABILITY DENSITY FUNCTIONS OF CLUSTERS IN FEATURE SPACE
Journal Title: International Journal of Advanced Research in Artificial Intelligence(IJARAI) - Year 2013, Vol 2, Issue 11
Abstract
Fisher distance based Genetic Algorithm: GA clustering method which takes into account overlapped space among probability density functions of clusters in feature space is proposed. Through experiments with simulation data of 2D and 3D feature space generated by random number generator, it is found that clustering performance depends on overlapped space among probability density function of clusters. Also it is found relation between cluster performance and the GA parameters, crossover and mutation probability as well as the number of features and the number of clusters.
Authors and Affiliations
Kohei Arai
Keywords
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