An Algorithm for the Learning of Weights in Discrimination Functions Using a Priori Constraints

Authors:
Norbert Krüger
Affiliations:
-
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
1997

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Abstract

We introduce a learning algorithm for the weights in a very common class of discrimination functions usually called "weighted average." The learning algorithm can reduce the number of free variables by simple but effective a priori criteria about significant features. Here we apply our algorithm to three tasks of different dimensionality all concerned with face recognition.