The maximal data piling direction for discrimination

Jeongyoun Ahn and J. S. Marron

Biometrika, 2010, vol. 97, issue 1, 254-259

Abstract: We study a discriminant direction vector that generally exists only in high-dimension, low sample size settings. Projections of data onto this direction vector take on only two distinct values, one for each class. There exist infinitely many such directions in the subspace generated by the data; but the maximal data piling vector has the longest distance between the projections. This paper investigates mathematical properties and classification performance of this discrimination method. Copyright 2010, Oxford University Press.

Date: 2010
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