Weighted linear programming discriminant analysis for high‐dimensional binary classification

DOI10.1002/sam.11473OpenAlexW3040201768MaRDI QIDQ4970346

Guan Yu, Yufei Wu

Publication date: 14 October 2020

Published in: Statistical Analysis and Data Mining: The ASA Data Science Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/sam.11473

zbMATH Keywords

linear programmingalternating direction method of multipliershigh dimensional datalinear discriminant analysisbinary classificationfeature screening

Mathematics Subject Classification ID

Statistics (62-XX) Computer science (68-XX)

Uses Software

• lp_solve
• lpSolve
• sda
• glmnet
• ElemStatLearn
• penalizedLDA
• sdwd

Cites Work

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• Sure independence screening in generalized linear models with NP-dimensionality
• High-dimensional classification using features annealed independence rules
• Some theory for Fisher's linear discriminant function, `naive Bayes', and some alternatives when there are many more variables than observations
• Penalized Classification using Fisher’s Linear Discriminant
• A direct approach to sparse discriminant analysis in ultra-high dimensions
• A Direct Estimation Approach to Sparse Linear Discriminant Analysis
• Sure Independence Screening for Ultrahigh Dimensional Feature Space
• The Kolmogorov filter for variable screening in high-dimensional binary classification
• Comparison of Discrimination Methods for High Dimensional Data
• A Road to Classification in High Dimensional Space: The Regularized Optimal Affine Discriminant

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