Title

ENN: Extended Nearest Neighbor Method for Pattern Recognition [Research Frontier]

Document Type

Article

Date of Original Version

8-1-2015

Abstract

This article introduces a new supervised classification method-the extended nearest neighbor (ENN)-that predicts input patterns according to the maxiμm gain of intra-class coherence. Unlike the classic k-nearest neighbor (KNN) method, in which only the nearest neighbors of a test sample are used to estimate a group membership, the ENN method makes a prediction in a two-way communication style: it considers not only who are the nearest neighbors of the test sample, but also who consider the test sample as their nearest neighbors. By exploiting the generalized class-wise statistics from all training data by iteratively assuming all the possible class memberships of a test sample, the ENN is able to learn from the global distribution, therefore improving pattern recognition performance and providing a powerful technique for a wide range of data analysis applications.

Publication Title

IEEE Computational Intelligence Magazine

Volume

10

Issue

3

Share

COinS