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A dimensionality reduction approach for the visualization of the cluster space: A trustworthiness evaluation

Griparis, Andreea and Faur, Daniela and Datcu, Mihai (2016) A dimensionality reduction approach for the visualization of the cluster space: A trustworthiness evaluation. In: Proceedings of IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2016, pp. 2917-2920. IEEE Xplore. IGARSS 2016, 10-15 July 2016, Beijing, China. DOI: 10.1109/IGARSS.2016.7729753 ISBN 978-1-5090-3332-4 ISSN 2153-7003

Full text not available from this repository.

Official URL: http://ieeexplore.ieee.org/document/7729753/

Abstract

The data mining systems solve the problem of handling Earth Observation archives counting on a feature vectors based description of the data. Increasing the dimensionality of the feature vectors would offer an effective perspective of the dataset's content. The modern systems provide visual exploration of data projecting their high-dimensional feature space in a 3-D space. The dimensionality reduction methods represent the main way to achieve such representation. Several dimensionality reduction methods have been proposed to identify the mapping, bot not all of them retain the same dataset properties. In order to compare their performance, the development of formal measures like “Trustworthiness” or the measures based on Co-ranking matrix was mandatory. These measures objectively evaluate the similarity between the structure detected in the original and the reduced space. In this paper we evaluate six dimensionality reduction methods using “Trustworthiness” and “Continuity” measures. In this regard three datasets have been used: an artificial one and two remote sensing datasets. Each of them have been described by a high-dimensional feature space.

Item URL in elib:https://elib.dlr.de/108042/
Document Type:Conference or Workshop Item (Poster)
Title:A dimensionality reduction approach for the visualization of the cluster space: A trustworthiness evaluation
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Griparis, AndreeaUniversity Politehnica BucharestUNSPECIFIED
Faur, DanielaUniversity Politehnica BucharestUNSPECIFIED
Datcu, Mihaimihai.datcu (at) dlr.deUNSPECIFIED
Date:13 July 2016
Journal or Publication Title:Proceedings of IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2016
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI :10.1109/IGARSS.2016.7729753
Page Range:pp. 2917-2920
Publisher:IEEE Xplore
ISSN:2153-7003
ISBN:978-1-5090-3332-4
Status:Published
Keywords:Dimesionality, reduction, visualization, evaluation, trustworthiness, continuity
Event Title:IGARSS 2016
Event Location:Beijing, China
Event Type:international Conference
Event Dates:10-15 July 2016
Organizer:IEEE Org.
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Dumitru, Corneliu Octavian
Deposited On:18 Nov 2016 12:18
Last Modified:24 Nov 2016 18:47

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