Model selection with PLANN-CR-ARD

Corneliu T C Arsene, Paulo J. Lisboa, Elia Biganzoli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a new compensation mechanism to be used with a Partial Logistic Artificial Neural Network for Competing Risks with Automatic Relevance Determination (PLANN-CR-ARD) and tested comprehensibly on a real breast cancer dataset with excellent convergence properties and numerical stability for the non-linear model. The Model Selection is implemented for the PLANN-CR-ARD model, benefiting from a scaling of the prior error term which together with the data error term forms the total error function that is optimized. The PLANN-CR-ARD proves to be an excellent prognostic tool that can be used in regression analysis tasks such as the survival analysis of cancer datasets.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages210-219
Number of pages10
Volume6692 LNCS
EditionPART 2
DOIs
Publication statusPublished - 2011
Event11th International Work-Conference on on Artificial Neural Networks, IWANN 2011 - Torremolinos-Malaga, Spain
Duration: Jun 8 2011Jun 10 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6692 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other11th International Work-Conference on on Artificial Neural Networks, IWANN 2011
CountrySpain
CityTorremolinos-Malaga
Period6/8/116/10/11

Keywords

  • Artificial Neural Networks
  • Competing Risks
  • Convergence properties
  • Model Selection
  • PLANN-CR-ARD

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    Arsene, C. T. C., Lisboa, P. J., & Biganzoli, E. (2011). Model selection with PLANN-CR-ARD. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 2 ed., Vol. 6692 LNCS, pp. 210-219). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6692 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-21498-1_27