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.

Citation

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

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