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Distance-weighted discrimination
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OA
AI
DOI：10.1198/016214507000001120.png)
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摘要
En 中文
High-dimension low-sample size statistical analysis is becoming increasingly important in a wide range of applied contexts. In such situations, 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.
Keyword:
classification
high-dimension low sample size
support vector machine
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论文数:
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被引数:
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