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Author Jaume Gibert; Ernest Valveny; Oriol Ramos Terrades; Horst Bunke
Title Multiple Classifiers for Graph of Words Embedding Type Conference Article
Year (down) 2011 Publication 10th International Conference on Multiple Classifier Systems Abbreviated Journal
Volume 6713 Issue Pages 36-45
Keywords
Abstract During the last years, there has been an increasing interest in applying the multiple classifier framework to the domain of structural pattern recognition. Constructing base classifiers when the input patterns are graph based representations is not an easy problem. In this work, we make use of the graph embedding methodology in order to construct different feature vector representations for graphs. The graph of words embedding assigns a feature vector to every graph by counting unary and binary relations between node representatives and combining these pieces of information into a single vector. Selecting different node representatives leads to different vectorial representations and therefore to different base classifiers that can be combined. We experimentally show how this methodology significantly improves the classification of graphs with respect to single base classifiers.
Address Napoles, Italy
Corporate Author Thesis
Publisher Place of Publication Editor Carlo Sansone; Josef Kittler; Fabio Roli
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-642-21556-8 Medium
Area Expedition Conference MCS
Notes DAG Approved no
Call Number Admin @ si @GVR2011 Serial 1745
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Author Miguel Angel Bautista; Oriol Pujol; Xavier Baro; Sergio Escalera
Title Introducing the Separability Matrix for Error Correcting Output Codes Coding Type Conference Article
Year (down) 2011 Publication 10th International conference on Multiple Classifier Systems Abbreviated Journal
Volume 6713 Issue Pages 227-236
Keywords
Abstract Error Correcting Output Codes (ECOC) have demonstrate to be a powerful tool for treating multi-class problems. Nevertheless, predefined ECOC designs may not benefit from Error-correcting principles for particular multi-class data. In this paper, we introduce the Separability matrix as a tool to study and enhance designs for ECOC coding. In addition, a novel problem-dependent coding design based on the Separability matrix is tested over a wide set of challenging multi-class problems, obtaining very satisfactory results.
Address Napoles, Italy
Corporate Author Thesis
Publisher Springer-Verlag Berlin Heidelberg Place of Publication Editor Carlo Sansone; Josef Kittler; Fabio Roli
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-642-21556-8 Medium
Area Expedition Conference MCS
Notes MILAB; OR;HuPBA;MV Approved no
Call Number Admin @ si @ BPB2011a Serial 1771
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Author Eloi Puertas; Sergio Escalera; Oriol Pujol
Title Multi-Class Multi-Scale Stacked Sequential Learning Type Conference Article
Year (down) 2011 Publication 10th International Conference on Multiple Classifier Systems Abbreviated Journal
Volume 6713 Issue Pages 197-206
Keywords
Abstract
Address Napoles, Italy
Corporate Author Thesis
Publisher Springer Place of Publication Editor Carlo Sansone; Josef Kittler; Fabio Roli
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference MCS
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ PEP2011b Serial 1772
Permanent link to this record
 

 
Author Miguel Angel Bautista; Oriol Pujol; Xavier Baro; Sergio Escalera
Title Introducing the Separability Matrix for Error Correcting Output Codes Coding Type Conference Article
Year (down) 2011 Publication 10th International Conference on Multiple Classifier Systems Abbreviated Journal
Volume 6713 Issue Pages 227-236
Keywords
Abstract Error Correcting Output Codes (ECOC) have demonstrate to be a powerful tool for treating multi-class problems. Nevertheless, predefined ECOC designs may not benefit from Error-correcting principles for particular multi-class data. In this paper, we introduce the Separability matrix as a tool to study and enhance designs for ECOC coding. In addition, a novel problem-dependent coding design based on the Separability matrix is tested over a wide set of challenging multi-class problems, obtaining very satisfactory results.
Address Napoles, Italy
Corporate Author Thesis
Publisher Springer-Verlag Berlin, Heidelberg Place of Publication Editor Carlo Sansone; Josef Kittler; Fabio Roli
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-21556-8 Medium
Area Expedition Conference MCS
Notes MILAB; OR;HuPBA;MV Approved no
Call Number Admin @ si @ BPB2011b Serial 1887
Permanent link to this record