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Immersive Visualization of the Quality of Dimensionality Reduction : Volume Xl-1/W3, Issue 1 (24/09/2013)

By Babaee, M.

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Book Id: WPLBN0004014533
Format Type: PDF Article :
File Size: Pages 5
Reproduction Date: 2015

Title: Immersive Visualization of the Quality of Dimensionality Reduction : Volume Xl-1/W3, Issue 1 (24/09/2013)  
Author: Babaee, M.
Volume: Vol. XL-1/W3, Issue 1
Language: English
Subject: Science, Isprs, International
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus Publications
Publication Date:
Publisher: Copernicus Publications, Göttingen, Germany
Member Page: Copernicus Publications


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Datcu, M., Rigoll, G., & Babaee, M. (2013). Immersive Visualization of the Quality of Dimensionality Reduction : Volume Xl-1/W3, Issue 1 (24/09/2013). Retrieved from

Description: Institute for Human-Machine Communication, Technische Universität München, Munich Aerospace Faculty, Munich, Germany. Dimensionality reduction is the most widely used approach for extracting the most informative low-dimensional features from highdimensional ones. During the last two decades, different techniques (linear and nonlinear) have been proposed by researchers in various fields. However, the main question is now how well a specific technique does this job. In this paper, we introduce a qualitative method to assess the quality of dimensionality reduction. In contrast to numerical assessment, we focus here on visual assessment. We visualize the Minimum Spanning Tree (MST) of neighborhood graphs of data before and after dimensionality reduction in an immersive 3D virtual environment. We employe a mixture of linear and nonlinear dimension reduction techniques to apply to both synthetic and real datasets. The visualization depicts the quality of each technique in term of preserving distances and neighborhoods. The results show that a specific dimension reduction technique exhibits different performance in dealing with different datasets.



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