DocumentCode :
918591
Title :
A confidence model for finite-memory learning systems (Corresp.)
Author :
Horos, John A. ; Hellman, Martin E.
Volume :
18
Issue :
6
fYear :
1972
fDate :
11/1/1972 12:00:00 AM
Firstpage :
811
Lastpage :
813
Abstract :
A confidence model for finite-memory learning systems is advanced in this correspondence. The primary difference between this and the previously used probability-of-error model is that a measure of confidence is associated with each decision and any incorrect decisions are weighted according to their confidence measure in figuring total loss. The optimal rule for this model is deterministic, whereas the previous model required randomized rules to achieve minimum error probability.
Keywords :
Finite-memory methods; Hypothesis testing; Learning procedures; Algebra; Equations; Error probability; Learning systems; Loss measurement; Matrices; Probability density function; Random variables; Statistics; Testing;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.1972.1054918
Filename :
1054918
Link To Document :
بازگشت