COMPARISON OF PURITY AND ENTROPY OF K-MEANS CLUSTERING AND FUZZY C MEANS CLUSTERING
Satya Chaitanya Sripada · 2011
Clustering is one the main area in data mining literature. There are various algorithms for clustering. The evaluation of the performance is done by validation measures. The external validation measures are used to measure the extent to which cluster labels affirm with the externally given class labels. The aim of this paper is to compare the for K-means and Fuzzy C means clustering using the Purity and Entropy. The data used for evaluating the external measures is medical data.