Irrelevant Features in Pattern Recognition

Authors:
M. Ben-Bassat
Affiliations:
USC Center for the Critically Ill, Shock Research Unit
Venue:
IEEE Transactions on Computers
Year:
1978

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Abstract

The concept of irrelevant features in Bayesian models for pattern recognition is introduced, and its mathematical meaning is explained. A technique for computing the conditional probabilities of irrelevant features, if necessary, is described. The effect of irrelevant features on feature selection in sequential classification is discussed and illustrated.