Modified center-based feature line classification approach

Abstract

A novel classification approach called modified center-based feature line (MCFL) is proposed to reduce the computational cost of the nearest feature line (NFL) and maintain the advantages of NFL. Unlike NFL, MCFL defines a different type of feature line and utilizes both the query point’s local information and corresponding class-global information in training set. In experiments provided, the comparisons with the nearest neighbor (NN), NFL, and other NFL-refined approaches show that the computation time of MCFL can be shortened dramatically with less accuracy decreases. MCFL proposed is probably a better choice for the classification application tasks of large-scale dataset.

Key words： classification; nearest feature line (NFL); nearest neighbor line (NNL); center-based nearest neighbor (CNN); modified center-based feature line (MCFL)