Treffer: Simultaneous features and objects selection for mixed and incomplete data
Title:
Simultaneous features and objects selection for mixed and incomplete data
Authors:
Source:
Progress in pattern recognition, image analysis and applications (11th Iberoamerican congress in pattern recognition, CIARP 2006, Cancun, Mexico, November 14-17, 2006)0CIARP 2006. :597-605
Publisher Information:
Berlin; Heidelberg; New York: Springer, 2006.
Publication Year:
2006
Physical Description:
print, 12 ref 1
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Logiciel, Software, Organisation des mémoires. Traitement des données, Memory organisation. Data processing, Systèmes d'information. Bases de données, Information systems. Data bases, Intelligence artificielle, Artificial intelligence, Reconnaissance des formes. Traitement numérique des images. Géométrie algorithmique, Pattern recognition. Digital image processing. Computational geometry, Base donnée orientée objet, Object-oriented databases, Base donnée, Database, Base dato, Classification, Clasificación, Donnée manquante, Missing data, Dato que falta, Information incomplète, Incomplete information, Información incompleta, Mélangeage, Mixing, Mezclado, Méthode projection, Projection method, Método proyección, Reconnaissance forme, Pattern recognition, Reconocimiento patrón, Théorie ensemble, Set theory, Teoría conjunto, Traitement image, Image processing, Procesamiento imagen
Document Type:
Konferenz
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
University of Ciego de Ávila, Cuba
Bioplants Center, UNICA, C. de Ávila, Cuba
Advanced Technologies Applications Center, Minbas, Cuba
Bioplants Center, UNICA, C. de Ávila, Cuba
Advanced Technologies Applications Center, Minbas, Cuba
ISSN:
0302-9743
Rights:
Copyright 2007 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.19078994
Database:
PASCAL Archive
Weitere Informationen
, In this paper a new simultaneous editing and feature selection method for the Most Similar Neighbor classifier is proposed. It is designed for databases with objects described by features no exclusively numeric or categorical. It is based on Testor Theory and the Compact Set Editing method, mixing edited projections until a good accuracy is achieved. Experimental results with several databases show a good performance compared to previous methods and the classifier using the original sample.