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Spatial Distance Preservation based Methods for Non-Linear Dimensionality Reduction

by Rashmi Gupta, Pooja Pandey, Rajiv Kapoor
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 69 - Number 20
Year of Publication: 2013
Authors: Rashmi Gupta, Pooja Pandey, Rajiv Kapoor
10.5120/12090-8281

Rashmi Gupta, Pooja Pandey, Rajiv Kapoor . Spatial Distance Preservation based Methods for Non-Linear Dimensionality Reduction. International Journal of Computer Applications. 69, 20 ( May 2013), 37-41. DOI=10.5120/12090-8281

@article{ 10.5120/12090-8281,
author = { Rashmi Gupta, Pooja Pandey, Rajiv Kapoor },
title = { Spatial Distance Preservation based Methods for Non-Linear Dimensionality Reduction },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 69 },
number = { 20 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 37-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume69/number20/12090-8281/ },
doi = { 10.5120/12090-8281 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:30:51.126299+05:30
%A Rashmi Gupta
%A Pooja Pandey
%A Rajiv Kapoor
%T Spatial Distance Preservation based Methods for Non-Linear Dimensionality Reduction
%J International Journal of Computer Applications
%@ 0975-8887
%V 69
%N 20
%P 37-41
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The preservation of the pairwise distances measured in a data set ensures that the low dimensional embedding inherits the main geometric properties of the data like the local neighborhood relationships. In this paper, distance preserving technique namely, Sammons nonlinear mapping (Sammon's NLM) and Curvilinear Component Analysis (CCA) have been discussed and compared for non-linear dimensionality reduction. Basic principle in both the technique is that local neighborhood relationship is maintained. The results have beencompared for both the techniques on artificially generated data set using MATLAB software.

References
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Index Terms

Computer Science
Information Sciences

Keywords

MDS Dimensionality Reduction Nonlinear Mapping Vector Quantization Quasi Newton Optimization Gradient Descent

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