Sure feature screening for high-dimensional dichotomous classification

DOI10.1007/s11425-016-0117-3zbMath1360.62081OpenAlexW2557486581MaRDI QIDQ525910

Li Shao, Yuan Yu, Yong Zhou

Publication date: 5 May 2017

Published in: Science China. Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11425-016-0117-3

zbMATH Keywords

sure screening propertydichotomous classificationultra-high dimensional data

Mathematics Subject Classification ID

Reliability, availability, maintenance, inspection in operations research (90B25) Statistical ranking and selection procedures (62F07)

Related Items (1)

Robust Feature Screening via Distance Correlation for Ultrahigh Dimensional Data With Responses Missing at Random

Cites Work

• Measuring and testing dependence by correlation of distances
• Model-Free Feature Screening for Ultrahigh-Dimensional Data
• Robust rank correlation based screening
• High-dimensional classification using features annealed independence rules
• Nonparametric feature screening
• Weak convergence and empirical processes. With applications to statistics
• Asymptotic properties of bridge estimators in sparse high-dimensional regression models
• Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Additive Models
• Tables of the cramér-von mises distributions
• Sure Independence Screening for Ultrahigh Dimensional Feature Space
• Feature Screening via Distance Correlation Learning
• Probability Inequalities for Sums of Bounded Random Variables
• Model-Free Feature Screening for Ultrahigh Dimensional Discriminant Analysis
• The Kolmogorov filter for variable screening in high-dimensional binary classification
• Convergence of stochastic processes

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