Treffer: Two contributions of constraint programming to machine learning
Title:
Two contributions of constraint programming to machine learning
Authors:
Source:
Foundations of security analysis and design III (FOSAD 2004/2005 Tutorial lectures)Lecture notes in computer science. :617-624
Publisher Information:
New York, NY: Springer, 2005.
Publication Year:
2005
Physical Description:
print, 14 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, Intelligence artificielle, Artificial intelligence, Apprentissage et systèmes adaptatifs, Learning and adaptive systems, Algorithme apprentissage, Learning algorithm, Algoritmo aprendizaje, Programmation logique avec contrainte, Constraint logic programming, Programación lógica con restricción, Programmation mathématique, Mathematical programming, Programación matemática, Système aide décision, Decision support system, Sistema ayuda decisíon, Apprentissage machine, Machine learning
Document Type:
Konferenz
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Université d'Orléans-LIFO, BP6759, 45067 Orléans, France
ISSN:
0302-9743
Rights:
Copyright 2006 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.17324824
Database:
PASCAL Archive
Weitere Informationen
A constraint is a relation with an active behavior. For a given relation, we propose to learn a representation adapted to this active behavior. It yields two contributions. The first is a generic meta-technique for classifier improvement showing performances comparable to boosting. The second lies in the ability of using the learned concept in constraint-based decision or optimization problems. It opens a new way of integrating Machine Learning in Decision Support Systems.