Abstract
We propose a semiparametric linear programming discriminant (SLPD) rule for high dimensional discriminant analysis under a semiparametric model. As an extension, we further propose a two-stage SLPD (TSLPD) rule, which can have better classification performance under mild sparsity assumptions.
| Original language | English |
|---|---|
| Pages (from-to) | 103-110 |
| Number of pages | 8 |
| Journal | Statistics and Probability Letters |
| Volume | 110 |
| DOIs | |
| Publication status | Published - 1 Mar 2016 |
Keywords
- Bayes rule
- Linear discrimination analysis
- Monotone transformation
- Semiparametric discriminant analysis
- Sparsity
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty
Fingerprint
Dive into the research topics of 'High dimensional discrimination analysis via a semiparametric model'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver