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NOW G-Net: Learning Classification Programs on Networks of Workstations
 

Summary: NOW G-Net: Learning Classification Programs on Networks of
Workstations
Cosimo Anglano1
, Marco Botta2
1
Dipartimento di Informatica, Universit`a del Piemonte Orientale
Spalto Marengo 33, 15100 Alessandria (Italy),
email: cosimo.anglano@unipmn.it
2
Dipartimento di Informatica, Universit`a di Torino
Corso Svizzera 185, 10149 Torino (Italy),
email: botta@di.unito.it
Abstract
The automatic construction of classifiers (programs able to correctly classify data collected
from the real world) is one of the major problems in pattern recognition and in a wide area related
to artificial intelligence, including data mining. In this paper, we present G-Net, a distributed
evolutionary algorithm able to infer classifiers from precollected data. The main features of the
system include robustness with respect to parameter settings, use of the minimum description
length (MDL) criterion coupled with a stochastic search bias, coevolution as high-level control
strategy, ability to face problems requiring structured representation languages, and suitability

  

Source: Anglano, Cosimo - Dipartimento di Informatica, UniversitÓ del Piemonte Orientale "A. Avogadro"

 

Collections: Computer Technologies and Information Sciences