Model Selection for Classification with a Large Number of Classes
From MaRDI portal
Publication:2787380
DOI10.1007/978-1-4939-0569-0_23zbMath1381.62164OpenAlexW216700734MaRDI QIDQ2787380
No author found.
Publication date: 25 February 2016
Published in: Springer Proceedings in Mathematics & Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-1-4939-0569-0_23
Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).
Cites Work
- Unnamed Item
- Unnamed Item
- Innovated higher criticism for detecting sparse signals in correlated noise
- Bayesian feature selection for classification with possibly large number of classes
- Global testing under sparse alternatives: ANOVA, multiple comparisons and the higher criticism
- High-dimensional classification using features annealed independence rules
- A uniform asymptotic expansion for the incomplete gamma function
- Higher criticism for detecting sparse heterogeneous mixtures.
- Detection boundary in sparse regression
- Estimation and confidence sets for sparse normal mixtures
This page was built for publication: Model Selection for Classification with a Large Number of Classes
