A multivariate algorithm for gene selection based on the nearest neighbor probability (Articolo in rivista)

Type
Label
  • A multivariate algorithm for gene selection based on the nearest neighbor probability (Articolo in rivista) (literal)
Anno
  • 2009-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1007/978-3-642-02504-4_11 (literal)
Alternative label
  • E. Ferrari, M. Muselli (2009)
    A multivariate algorithm for gene selection based on the nearest neighbor probability
    in Lecture notes in computer science
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • E. Ferrari, M. Muselli (literal)
Pagina inizio
  • 123 (literal)
Pagina fine
  • 131 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 5488 (literal)
Rivista
Note
  • ISI Web of Science (WOS) (literal)
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • E. Ferrari, M. Muselli: CNR-IEIIT, Italy (literal)
Titolo
  • A multivariate algorithm for gene selection based on the nearest neighbor probability (literal)
Abstract
  • A general constructive approach for training neural networks in classification problems is presented. This approach is used to construct a particular connectionist model, named Switching Neural Network (SNN), based on the conversion of the original problem in a Boolean lattice domain. The training of an SNN can be performed through a constructive algorithm, called Switch Programming (SP), based on the solution of a proper linear programming problem. Simulation results obtained on the StatLog benchmark show the good quality of the SNNs trained with SP. (literal)
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