Abstract
In this second part of the paper, we compare the cluster quality of K-means, GA K-means, rough K-means, GA rough K-means and GA rough K-medoid algorithms. We experimented with a real world data set, and a standard data set using total within cluster variation, precision and execution time as the measures of comparison.
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Joshi, M., Lingras, P. (2009). Evolutionary and Iterative Crisp and Rough Clustering II: Experiments. In: Chaudhury, S., Mitra, S., Murthy, C.A., Sastry, P.S., Pal, S.K. (eds) Pattern Recognition and Machine Intelligence. PReMI 2009. Lecture Notes in Computer Science, vol 5909. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11164-8_101
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DOI: https://doi.org/10.1007/978-3-642-11164-8_101
Publisher Name: Springer, Berlin, Heidelberg
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