The maximal data piling direction for discrimination
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.
Year of publication: |
2010
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Authors: | Ahn, Jeongyoun ; Marron, J. S. |
Published in: |
Biometrika. - Biometrika Trust, ISSN 0006-3444. - Vol. 97.2010, 1, p. 254-259
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Publisher: |
Biometrika Trust |
Saved in:
Online Resource
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