Accession Number : AD0763839

Title :   Convergence of the Edited Nearest Neighbor,

Corporate Author : TEXAS UNIV AUSTIN DEPT OF ELECTRICAL ENGINEERING

Personal Author(s) : Wagner,T. J.

Report Date : JUN 1973

Pagination or Media Count : 10

Abstract : The edited k-nearest neighbor rule (k-NNR) consists of eliminating those samples from the data which are not classified correctly by the k-NNR and the remainder of the data and using the NNR with the samples which remain from to classify new observations. Wilson has shown that this rule has an asymptotic probability of error which is better than the k-NNR. A key step in his development is showing the convergence of the edited nearest neighbor. His lengthy argument is replaced here by a somewhat simpler one which uses an intuitive fact about the editing procedure. (Author)

Descriptors :   (*STATISTICAL ANALYSIS, THEOREMS), SAMPLING, PROBABILITY DENSITY FUNCTIONS, RANDOM VARIABLES, CONVERGENCE, ASYMPTOTIC SERIES, THEOREMS

Subject Categories : Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE