alexa Efficient Feature Subset Selection Techniques for High
ISSN ONLINE(2320-9801) PRINT (2320-9798)

International Journal of Innovative Research in Computer and Communication Engineering
Open Access

OMICS International organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations

700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

Research Article

Efficient Feature Subset Selection Techniques for High Dimensional Data

Sherin Mary Varghese1 and M.N.Sushmitha2
  1. M.Tech Student, Department of CSE, Hindustan University, Chennai, India
  2. Assistant Professor , Department of CSE, Hindustan University, Chennai , India
Related article at Pubmed, Scholar Google
 

Abstract

A database can contain several dimensions or attributes. Many Clustering methods are designed for clustering low–dimensional data. In high dimensional space finding clusters of data objects is challenging due to the curse of dimensionality. When the dimensionality increases, data in the irrelevant dimensions may produce much noise and mask the real clusters to be discovered. To deal with these problems, an efficient feature subset selection technique for high dimensional data has been proposed. Feature subset selection reduces the data size by removing irrelevant or redundant attributes. This algorithm works in two different steps that is minimum spanning tree based clustering methods and representative feature cluster selection. The proposed Pearson correlation measure focused on minimized redundant data. As a result, only a small number of discriminative features are selected.

Keywords

Share This Page

Additional Info

Loading
Loading Please wait..
Peer Reviewed Journals
 
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
 
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

 
© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version
adwords