Sample size calculation from specified RMS of the resubstitution error for linear classifiers

Amin Zollanvari, Ulisses M. Braga-Neto, Edward R. Dougherty

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

1 Citation (Scopus)

Abstract

Error estimation must be used to find the accuracy of a designed classifier, an issue that is critical in biomarker discovery. This paper applies analytical results derived previously by the authors concerning the exact sampling distribution of resubstitution for LDA under a Gaussianity assumption in order to investigate how the RMS for resubstitution behaves as a function of sample size. In particular, this allows one to make simple sample-size calculations based on a specified RMS.

Original languageEnglish
Title of host publication2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009
DOIs
Publication statusPublished - Oct 2 2009
Event2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009 - Minneapolis, MN, United States
Duration: May 17 2009May 21 2009

Publication series

Name2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009

Other

Other2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009
CountryUnited States
CityMinneapolis, MN
Period5/17/095/21/09

ASJC Scopus subject areas

  • Molecular Biology
  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition
  • Biomedical Engineering

Fingerprint Dive into the research topics of 'Sample size calculation from specified RMS of the resubstitution error for linear classifiers'. Together they form a unique fingerprint.

  • Cite this

    Zollanvari, A., Braga-Neto, U. M., & Dougherty, E. R. (2009). Sample size calculation from specified RMS of the resubstitution error for linear classifiers. In 2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009 [5174333] (2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009). https://doi.org/10.1109/GENSIPS.2009.5174333