Title :
Predicting the Required Number of Training Samples
Author :
Kalayeh, H.M. ; Landgrebe, D.A.
Author_Institution :
Object Recognition Systems, Inc., Princeton, NJ 08540.
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 :
Character generation; Decision theory; Distributed computing; Error probability; Linear approximation; Mathematics; Pattern recognition; Probability distribution; Statistical analysis; Upper bound; Multivariate normal distribution; parameter estimation; training samples; transformed divergence;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.1983.4767459
