Abstract :
A direct method of measurement selection is proposed to determine the best subset of d measurements out of a set of D total measurements. The measurement subset evaluation procedure directly employs a nonparametric estimate of the probability of error given a finite design sample set. A suboptimum measurement subset search procedure is employed to reduce the number of subsets to be evaluated. Teh primary advantage of the approach is the direct but nonparametric evaluation of measurement subsets, for the M class problem.
Keywords :
Feature space evaluation, measurement (feature) selection, nearest neighbor rule, pattern classification.; Acoustic noise; Cities and towns; Engines; FAA; Maintenance; Notice of Violation; Pattern analysis; Pattern recognition; Signal analysis; Vibrations; Feature space evaluation, measurement (feature) selection, nearest neighbor rule, pattern classification.;
