Parsimony doesn't mean Simplicity: Genetic Programming for Inductive Inference on Noisy Data (Articolo in rivista)

Type
Label
  • Parsimony doesn't mean Simplicity: Genetic Programming for Inductive Inference on Noisy Data (Articolo in rivista) (literal)
Anno
  • 2007-01-01T00:00:00+01:00 (literal)
Alternative label
  • De Falco Ivanoe, Tarantino Ernesto, Scafuri Umberto, Della Cioppa Antonio, Maisto Domenico (2007)
    Parsimony doesn't mean Simplicity: Genetic Programming for Inductive Inference on Noisy Data
    in Lecture notes in computer science
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • De Falco Ivanoe, Tarantino Ernesto, Scafuri Umberto, Della Cioppa Antonio, Maisto Domenico (literal)
Pagina inizio
  • 351 (literal)
Pagina fine
  • 360 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 4445- (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
  • titolo del volume: Genetic Programming, Marc Ebner et al. editors, ISBN 978-3-540-71602-0 (literal)
Note
  • ISI Web of Science (WOS) (literal)
Titolo
  • Parsimony doesn't mean Simplicity: Genetic Programming for Inductive Inference on Noisy Data (literal)
Abstract
  • A Genetic Programming algorithm based on Solomonoff's probabilistic induction is designed and used to face an Inductive Inference task, i.e., symbolic regression. To this aim, some test functions are dressed with increasing levels of noise and the algorithm is employed to denoise the resulting function and recover the starting functions. Then, the algorithm is compared against a classical parsimony-based GP. The results shows the superiority of the Solomonoff-based approach. (literal)
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