Title :
Statistical Properties of Error Estimators in Performance Assessment of Recognition Systems
Author :
Kittler, J. ; Devijver, P.A.
Author_Institution :
Technology Division, SERC Rutherford and Appleton Laboratories, Chilton, England.
fDate :
3/1/1982 12:00:00 AM
Abstract :
The problem of estimating the error probability of a given classification system is considered. Statistical properties of the empirical error count (C) and the average conditional error (R) estimators are studied. It is shown that in the large sample case the R estimator is unbiased and its variance is less than that of the C estimator. In contrast to conventional methods of Bayes error estimation the unbiasedness of the R estimator for a given classifier can be obtained only at the price of an additional set of classified samples. On small test sets the R estimator may be subject to a pessimistic bias caused by the averaging phenomenon characterizing the functioning of conditional error estimators.
Keywords :
Error analysis; Error probability; Estimation error; Laboratories; Pattern analysis; Pattern recognition; System analysis and design; System performance; Testing; Yield estimation; Average conditional error estimator; classification error probability; empirical error count estimator;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.1982.4767229