Title :
Irrelevant Features in Pattern Recognition
Author :
Ben-Bassat, Moshe
Author_Institution :
USC Center for the Critically Ill, Shock Research Unit
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.
Keywords :
Classification; irrelevant features; pattern recognition; probability of error; sequential decision-making systems; Bayesian methods; Decision making; Distributed computing; Heart; Lungs; Mathematical model; Pattern recognition; Public healthcare; Waste materials; Yield estimation; Classification; irrelevant features; pattern recognition; probability of error; sequential decision-making systems;
Journal_Title :
Computers, IEEE Transactions on
DOI :
10.1109/TC.1978.1675182
