INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
A. Surekha
, S. Anuradha , B. Jaya Lakshmi , K. B. Madhuri
Unique Id:
IJSDR1608040
Published In:
Volume 1 Issue 8, August-2016
Abstract:
Abstract---Subspace clustering is an extension to traditional clustering that seeks to find clusters in different subspaces within a dataset. Subspace clustering finds sets of objects that are homogeneous in subspaces of high-dimensional datasets, and has been successfully applied in many domains. Often in high dimensional data, many dimensions may be irrelevant and can mask real clusters. Subspace clustering algorithms localize the search process for relevant dimensions allowing them to find clusters that exist in various subspaces. Subspace clustering can be categorized into hard subspace clustering (HSC) and soft subspace clustering (SSC). HSC algorithms assume that each dimension in the data set has equal importance in the process of clustering, while SSC algorithms deal with feature weighing based on its contribution. Based on the direction of exploration of subspace clusters, HSC algorithms could be classified into two main categories: Top-down and Bottom-up. Top-down algorithms find an initial clustering in the full set of dimensions and evaluate the subspaces of each cluster, iteratively improving the results. Bottom-up approaches find dense regions in low dimensional spaces and combine them to form clusters. This paper surveys various hard subspace clustering algorithms and their efficacies, insufficiencies and recent developments. The readers would be provided with clear outline about the existing algorithms and nurture further developments and significant research in the area.
Keywords:
Subspace clustering, Hard subspace clustering, Top-down approach, Bottom-up approach
Cite Article:
"A survey on hard subspace clustering algorithms", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.1, Issue 8, page no.321 - 326, August-2016, Available :http://www.ijsdr.org/papers/IJSDR1608040.pdf
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Publication Details:
Published Paper ID: IJSDR1608040
Registration ID:160702
Published In: Volume 1 Issue 8, August-2016
DOI (Digital Object Identifier):
Page No: 321 - 326
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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