Predicting the Required Number of Training Samples

31 May 1983

journal article
Published by Institute of Electrical and Electronics Engineers (IEEE)

Vol. PAMI-5 (6) , 664-667
https://doi.org/10.1109/tpami.1983.4767459

Abstract

In this paper a criterion which measures the quality of the estimate of the covariance matrix of a multivariate normal distribution is developed. Based on this criterion, the necessary number of training samples is predicted. Experimental results which are used as a guide for determining the number of training samples are included.

Keywords

UPPER BOUND
PROBABILITY DISTRIBUTION
PATTERN RECOGNITION
MATHEMATICS
DISTRIBUTED COMPUTING
LINEAR APPROXIMATION
CHARACTER GENERATION
STATISTICAL ANALYSIS
ERROR PROBABILITY
DECISION THEORY

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