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Reseach Article

Axes Re-Ordering in Parallel Coordinate for Pattern Optimization

by Hemant Makwana, Sanjay Tanwani, Suresh Jain
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 40 - Number 13
Year of Publication: 2012
Authors: Hemant Makwana, Sanjay Tanwani, Suresh Jain
10.5120/5044-7370

Hemant Makwana, Sanjay Tanwani, Suresh Jain . Axes Re-Ordering in Parallel Coordinate for Pattern Optimization. International Journal of Computer Applications. 40, 13 ( February 2012), 43-48. DOI=10.5120/5044-7370

@article{ 10.5120/5044-7370,
author = { Hemant Makwana, Sanjay Tanwani, Suresh Jain },
title = { Axes Re-Ordering in Parallel Coordinate for Pattern Optimization },
journal = { International Journal of Computer Applications },
issue_date = { February 2012 },
volume = { 40 },
number = { 13 },
month = { February },
year = { 2012 },
issn = { 0975-8887 },
pages = { 43-48 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume40/number13/5044-7370/ },
doi = { 10.5120/5044-7370 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:28:01.601246+05:30
%A Hemant Makwana
%A Sanjay Tanwani
%A Suresh Jain
%T Axes Re-Ordering in Parallel Coordinate for Pattern Optimization
%J International Journal of Computer Applications
%@ 0975-8887
%V 40
%N 13
%P 43-48
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Visualization of multidimensional dataset is a challenging task due to non-uniformity of the data. It requires new ways to display data for better analysis and interpretation. Parallel coordinate is one of the popular techniques for visualization of multi dimensional dataset. Parallel coordinate technique emphasis various types of patterns present in the dataset. Here, pattern is shown by a poly-line. Slope of poly-line indicates the difference between data values. Variation in slope creates the different types of pattern. Based on slope, pattern can be classified and this kind of classification helps to explore distinct pattern available in dataset. Ordering of the axis affects pattern available in any dataset. Specific arrangement of axis may provide maximum patterns and another arrangement may provide minimum patterns. Ordering of axis in different order to find maximum or minimum pattern requires exponential time. Here, we propose a novel clustering technique using heuristic based branch & bound based axis reordering mechanism to solve this problem in polynomial time.

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Index Terms

Computer Science
Information Sciences

Keywords

Visualization Parallel Coordinates Cluttering Clustering Outlier pattren