DocumentCode :
249946
Title :
A Comparative Analysis of Various Cluster Detection Techniques for Data Mining
Author :
Vats, Prashant ; Mandot, Manju ; Gosain, Anjana
Author_Institution :
HMRITM, New Delhi, India
fYear :
2014
fDate :
9-11 Jan. 2014
Firstpage :
356
Lastpage :
361
Abstract :
Data mining is a knowledge discovery technique, used for exploring the new facts and relationships among data. It enables a user to uncover hidden information among available datasets. Cluster detection is one of the major techniques, which is used for data mining. In the Cluster detection techniques, User performs mining of data by searching for cluster of elements that are similar to each other. Each implementation of the cluster detection techniques adopts a method of comparing the value of individual datasets with those in their centroids. So, in this paper we have enlisted a few of them. Based on certain parameters, we have carried out a comprehensive analysis of various clustering techniques.
Keywords :
data mining; pattern clustering; cluster detection techniques; comparative analysis; comprehensive analysis; data mining; hidden information; knowledge discovery technique; Accuracy; Clustering algorithms; Data mining; Hidden Markov models; MATLAB; Noise; Spatial databases; Clusters; Data mining; Datasets; Patterns;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronic Systems, Signal Processing and Computing Technologies (ICESC), 2014 International Conference on
Conference_Location :
Nagpur
Type :
conf
DOI :
10.1109/ICESC.2014.67
Filename :
6745403
Link To Document :
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