APPROXIMATE EXPRESSIONS FOR THE VARIANCES OF NON-RANDOMIZED ERROR ESTIMATORS AND COD ESTIMATORS FOR THE DISCRETE HISTOGRAM RULE Conference Paper

abstract

• Estimation of the classification error and of the coefficient of determination (CoD) is a fundamental issue in discrete prediction problems. Analytical expressions for exact performance metrics of non-randomized error estimators and CoD estimators have been derived in previous publications by the authors. However, computation of these expressions becomes problematic as the sample size or predictor complexity increases, particularly in the case of second moments. Thus, fast and accurate approximations are desirable. In this paper, we make approximations to the variances of resubstitution and leave-one-out error estimators and CoD estimators. Our results show that these approximations not only are quite accurate but also reduce computation time tremendously. 2010 IEEE.

name of conference

• 2010 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS)

authors

• Braga Neto, Ulisses

published proceedings

• 2010 IEEE INTERNATIONAL WORKSHOP ON GENOMIC SIGNAL PROCESSING AND STATISTICS (GENSIPS)

author list (cited authors)

• Chen, T., & Braga-Neto, U.

citation count

• 0

complete list of authors

• Chen, Ting||Braga-Neto, Ulisses

publication date

• January 2010

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE International Workshop on Genomic Signal Processing and Statistics : [proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics  Journal

keywords

• Cod Estimation
• Discrete Histogram Rule
• Discrete Prediction
• Error Estimation

Digital Object Identifier (DOI)

• 10.1109/gensips.2010.5719673

International Standard Book Number (ISBN) 13

• 9781612847924

start page

• 1

end page

• 4

URL

• http://dx.doi.org/10.1109/gensips.2010.5719673