Distance Weighted Discrimination &
Geometrical Representation of High 
Dimension - Low Sample Size data

by J. S. Marron
UNC, Dept. of Statistics
& SAMSI

The Support Vector Machine is a discrimination method 
that was developed in the machine learning community.
Statistical ideas are used to improve it in the important
context of High Dimension - Low Sample Size data, 
resulting in a new method called Distance Weighted 
Discrimination.  The ideas are illustrated with some 
examples from micro-array analysis.  Some unexpected 
behavior is explained using a non-standard asymptotic 
analysis as the dimension tends to infinity.


