Table 3. Classes to cluster evaluation.

S.No	Clustering Models	Classes to Cluster Evaluation Accuracy (%)
		Pre- Hybrid feature selection	Post- Hybrid feature selection
1	E-M Algorithm	52.2124	51.3274
2	COBWEB	2.6549	5.3097
3	K-Means	53.0973	51.3274
4	Hierarchical Clustering	51.3274	51.3274
5	Density Based Clustering	53.0973	52.2124
6	Filtered Clustering	53.0973	51.3274
7	Farthest First Clustering	48.6726	46.0176