Clustering of Mixed data: A GKMM approach
Journal Title: International Journal of Advanced Biotechnology and Research. - Year 2016, Vol 7, Issue 2
Abstract
ABSTRACTClustering is important problem in data mining techniques. k-Means algorithm is one of the most capable and easy to employ clustering algorithm but having some difficulties i.e. applicable to numeric data, sensitive to the presence of noise and outliers and have initialisation issues. This paper proposed GKMM algorithm to cluster mixed data where the pre-processed data will be used for the clustering to overcome the limitation of local solution and handle only numeric data issues. This work is based on the concept of utilisation of numeric data based genetics clustering algorithm for mixed data and can be an easier alternative to reduce cost and helpful in optimizing performance. Moreover, decrease obvious sensitivity to the initial guess of the cluster centres.
Authors and Affiliations
Abha Sharma*1 and R. S. Thakur2
Keywords
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