Conditional characteristic feature screening for massive imbalanced data

DOI10.1007/s00362-022-01342-8MaRDI QIDQ6157042

No author found.

Publication date: 19 June 2023

Published in: Statistical Papers (Search for Journal in Brave)

zbMATH Keywords

ultrahigh dimensionalitycase-control samplingmodel-freeconditional characteristic screeningmassive imbalanced data

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Measuring and testing dependence by correlation of distances
• Sure independence screening in generalized linear models with NP-dimensionality
• Marginal empirical likelihood and sure independence feature screening
• Aggregated estimating equation estimation
• Local case-control sampling: efficient subsampling in imbalanced data sets
• Robust rank correlation based screening
• Distributed testing and estimation under sparse high dimensional models
• Model-free feature screening for ultrahigh dimensional censored regression
• Feature screening for multi-response varying coefficient models with ultrahigh dimensional predictors
• Quantile-adaptive model-free variable screening for high-dimensional heterogeneous data
• Fused variable screening for massive imbalanced data
• The fused Kolmogorov filter: a nonparametric model-free screening method
• Parametric Models for Response-Biased Sampling
• Censored rank independence screening for high-dimensional survival data
• Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Additive Models
• A split-and-conquer approach for analysis of
• Regression Analysis with Response-selective Sampling
• Sure Independence Screening for Ultrahigh Dimensional Feature Space
• Feature Screening via Distance Correlation Learning
• Optimal Subsampling for Large Sample Logistic Regression
• Feature Selection by Canonical Correlation Search in High-Dimensional Multiresponse Models With Complex Group Structures
• Category-Adaptive Variable Screening for Ultra-High Dimensional Heterogeneous Categorical Data
• Model-Free Feature Screening for Ultrahigh Dimensional Discriminant Analysis
• High Dimensional Ordinary Least Squares Projection for Screening Variables
• Partition-based ultrahigh-dimensional variable screening
• The Kolmogorov filter for variable screening in high-dimensional binary classification

This page was built for publication: Conditional characteristic feature screening for massive imbalanced data