Investigation Of Validity Metrics For Modified K-Meansclustering Algorithm
S Govinda Rao · i-manager s Journal on Computer Science · 2015
Clustering analysis is used to partition data set based on objects within a group and the clustering results are influenced by choice of distance measure and the clustering algorithm. Clustering analysis has been applied to group of author's hindex and g-index with similar or dissimilar features. Validity measure is calculated to determine which is the best clustering by finding the minimum value for our measure. In this paper, the authors have presented the effective validations possible with Davies-Bouldin index, Silhouette index and quantization error.