Two Phase Clustering Approach in Data Mining : A Review

Authors(2) :-Vashali, Shagun

In clustering, dissimilarity is measured between gadgets by way of measuring the Euclidean distance among every pair of items. Analysis of cluster is a descriptive assignment that perceive homogenous group of objects and it is also one of the fundamental analytical method in facts mining. mean Shift clustering does now not depend upon a priori information of the wide variety of clusters while ok-way algorithm is an unmanaged clustering set of rules that classifies the enter records factors into multiple clusters k based on their inherent distance from each other. On this assessment, the outline of mean shift and okay-way algorithm is provided.

Authors and Affiliations

Vashali
M. Tech. Scholar, Department of Computer Science & Engineering Manav Institutes of Technology & Management, Haryana, India
Shagun
Asstt. Professor, Department of Computer Science & Engineering Manav Institutes of Technology & Management, Haryana, India

huge statistics, SQL, BD

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Publication Details

Published in : Volume 3 | Issue 5 | May-June 2018
Date of Publication : 2018-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 726-731
Manuscript Number : CSEIT1835131
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Vashali, Shagun, "Two Phase Clustering Approach in Data Mining : A Review", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 5, pp.726-731, May-June-2018.
Journal URL : http://ijsrcseit.com/CSEIT1835131

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