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- Title
INVESTIGATION OF VALIDITY METRICS FOR MODIFIED K-MEANS CLUSTERING ALGORITHM.
- Authors
RAO, S. GOVINDA; GOVARDHAN, A.
- Abstract
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.
- Subjects
K-means clustering; CLUSTER analysis (Statistics); BIG data; DATA warehousing; DISTRIBUTED databases
- Publication
I-Manager's Journal on Computer Science, 2015, Vol 3, Issue 2, p33
- ISSN
2347-2227
- Publication type
Article
- DOI
10.26634/jcom.3.2.3548