Generalization in automatic learning using aggregation and prolongation - Archive ouverte HAL Accéder directement au contenu
Poster De Conférence Année : 1991

Generalization in automatic learning using aggregation and prolongation

Résumé

This paper is concerned with Automatic Symbolic Learning. More precisely, our aim is to extract rules describing the Input/Output behaviour of a system, from observations which might be incoherent. The presented approach traduces an orientated learning situation, in which the knowledge acquisition (model building) is made through the consideration of a set of examples (the data).
Fichier non déposé

Dates et versions

hal-01509951 , version 1 (18-04-2017)

Identifiants

  • HAL Id : hal-01509951 , version 1

Citer

Denis Pomorski, Marcel Staroswiecki. Generalization in automatic learning using aggregation and prolongation. Journées Internationales “Analyse de Données et Apprentissage Symbolique-Numérique”, Sep 1991, Paris, France. Journées Internationales “Analyse de Données et Apprentissage Symbolique-Numérique”. ⟨hal-01509951⟩

Collections

CNRS LAGIS
27 Consultations
0 Téléchargements

Partager

Gmail Facebook X LinkedIn More