Irrelevant Features in Pattern Recognition

Moshe Ben-Bassat*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)746-749
Number of pages4
JournalIEEE Transactions on Computers
Issue number8
StatePublished - Aug 1978
Externally publishedYes


Dive into the research topics of 'Irrelevant Features in Pattern Recognition'. Together they form a unique fingerprint.

Cite this