Distance Weighted Discrimination

High Dimension Low Sample Size statistical analysis is becoming increasingly important in a wide range of applied contexts. In such situations, it is seen that the popular Support Vector Machine suffers from ``data piling'' at the margin, which can diminish generalizability. This leads naturally to the development of Distance Weighted Discrimination, which is based on Second Order Cone Programming, a modern computationally intensive optimization method.


Technical Report No. 1339, School of Operations Research and Industrial Engineering, Cornell University (July 2002).



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