ISSN 2394-5125
 

Research Article 


EVD2BSCAN: ENHANCED VORONOI DIAGRAM DENSITY BASED CLUSTERING ALGORITHM FOR DATA CLUSTERING

T. KAVIPRIYA, Dr. M. SENGALIAPPAN.

Abstract
Clustering concern is a systematic approach for partitioning of data objects into matching clusters and typically regarded as unsupervised learning
problem. The real-time multiple constraints for objects are difficult to achieve for conventional algorithms. The appropriate cluster quantity from the
data attained by the distance-based clustering algorithm occurs in seldom manner autonomously. During clustering process, missing data problem is a
serious issue in many applications as it has significant effects the conclusion drawn from the data. The missing values and irrelevant data are resolved by
computing the mean of other data in either subject wise manner or student wise manner. In addition this work presents a Voronoi Diagram Density
Based Clustering Algorithm (VD2BSCAN) by fast search and determining density peaks. The input samples’ Voronoi diagram creation is a key factor in
retrieving the density information which is accomplished by the suggested VD2BSCAN. The corresponding parts of the instance space point density is
influenced directly by the point cells volume. The merging of densest parts of the instance space into clusters is achieved by scanning over the input
points and their Voronoi cells at a time. However, wide density variation inside the clusters is a serious concern to be considered in DBSCAN algorithm.
This issue is mitigated by enhanced EVD2BSCAN algorithm by estimation of growing Density Mean (DM) for some core object, in which density of its εneighborhood is considered with respect to DM has its own significance. The data are collected manually from the college placement departments for
the evaluation in R tool. The data are stored and fetched from Structured Query Language (SQL) database. The clustering performance metrics are
employed for the analysis of the performance. The EVD2BSCAN algorithm improves the clustering accuracy significantly compared than the DBSCAN,
Hierarchical Clustering (HC) analysis which is revealed by the evaluation results. The proposed algorithm outperforms well which can be utilized for
various applications.

Key words: Missing Data, Data Clustering, Enhanced Voronoi Diagram Density Based Clustering Algorithm (EVD2BSCAN), R Tool.


 
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How to Cite this Article
Pubmed Style

T. KAVIPRIYA, Dr. M. SENGALIAPPAN. EVD2BSCAN: ENHANCED VORONOI DIAGRAM DENSITY BASED CLUSTERING ALGORITHM FOR DATA CLUSTERING. JCR. 2020; 7(4): 1031-1036. doi:10.31838/jcr.07.04.193


Web Style

T. KAVIPRIYA, Dr. M. SENGALIAPPAN. EVD2BSCAN: ENHANCED VORONOI DIAGRAM DENSITY BASED CLUSTERING ALGORITHM FOR DATA CLUSTERING. http://www.jcreview.com/?mno=99138 [Access: June 02, 2021]. doi:10.31838/jcr.07.04.193


AMA (American Medical Association) Style

T. KAVIPRIYA, Dr. M. SENGALIAPPAN. EVD2BSCAN: ENHANCED VORONOI DIAGRAM DENSITY BASED CLUSTERING ALGORITHM FOR DATA CLUSTERING. JCR. 2020; 7(4): 1031-1036. doi:10.31838/jcr.07.04.193



Vancouver/ICMJE Style

T. KAVIPRIYA, Dr. M. SENGALIAPPAN. EVD2BSCAN: ENHANCED VORONOI DIAGRAM DENSITY BASED CLUSTERING ALGORITHM FOR DATA CLUSTERING. JCR. (2020), [cited June 02, 2021]; 7(4): 1031-1036. doi:10.31838/jcr.07.04.193



Harvard Style

T. KAVIPRIYA, Dr. M. SENGALIAPPAN (2020) EVD2BSCAN: ENHANCED VORONOI DIAGRAM DENSITY BASED CLUSTERING ALGORITHM FOR DATA CLUSTERING. JCR, 7 (4), 1031-1036. doi:10.31838/jcr.07.04.193



Turabian Style

T. KAVIPRIYA, Dr. M. SENGALIAPPAN. 2020. EVD2BSCAN: ENHANCED VORONOI DIAGRAM DENSITY BASED CLUSTERING ALGORITHM FOR DATA CLUSTERING. Journal of Critical Reviews, 7 (4), 1031-1036. doi:10.31838/jcr.07.04.193



Chicago Style

T. KAVIPRIYA, Dr. M. SENGALIAPPAN. "EVD2BSCAN: ENHANCED VORONOI DIAGRAM DENSITY BASED CLUSTERING ALGORITHM FOR DATA CLUSTERING." Journal of Critical Reviews 7 (2020), 1031-1036. doi:10.31838/jcr.07.04.193



MLA (The Modern Language Association) Style

T. KAVIPRIYA, Dr. M. SENGALIAPPAN. "EVD2BSCAN: ENHANCED VORONOI DIAGRAM DENSITY BASED CLUSTERING ALGORITHM FOR DATA CLUSTERING." Journal of Critical Reviews 7.4 (2020), 1031-1036. Print. doi:10.31838/jcr.07.04.193



APA (American Psychological Association) Style

T. KAVIPRIYA, Dr. M. SENGALIAPPAN (2020) EVD2BSCAN: ENHANCED VORONOI DIAGRAM DENSITY BASED CLUSTERING ALGORITHM FOR DATA CLUSTERING. Journal of Critical Reviews, 7 (4), 1031-1036. doi:10.31838/jcr.07.04.193