JCOM_V3_N2_RP5
Investigation of Validity Metrics for Modified K-Means Clustering Algorithm
S. Govinda Rao
A. Govardhan
Journal on Computer Science
2347–6141
3
2
33
36
Validity Measure, Davies-Bouldin Index, Silhouette Index, Quantization Error
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.
June - August 2015
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