Fused variable screening for massive imbalanced data

DOI10.1016/j.csda.2019.06.013OpenAlexW2959078919WikidataQ127534055 ScholiaQ127534055MaRDI QIDQ2008001

Jinhan Xie, Yuanyuan Lin, Wenxin Liu, Meiling Hao

Publication date: 22 November 2019

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2019.06.013

zbMATH Keywords

high dimensionrank correlationimbalanced datacase-control samplingmodel-free screening

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items

New hard-thresholding rules based on data splitting in high-dimensional imbalanced classification ⋮ Conditional characteristic feature screening for massive imbalanced data

Uses Software

• SMOTE

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Model-Free Feature Screening for Ultrahigh-Dimensional Data
• Sure independence screening in generalized linear models with NP-dimensionality
• The Adaptive Lasso and Its Oracle Properties
• Marginal empirical likelihood and sure independence feature screening
• Local case-control sampling: efficient subsampling in imbalanced data sets
• Robust rank correlation based screening
• Principled sure independence screening for Cox models with ultra-high-dimensional covariates
• Censored cumulative residual independent screening for ultrahigh-dimensional survival data
• Feature selection of ultrahigh-dimensional covariates with survival outcomes: a selective review
• Correlation rank screening for ultrahigh-dimensional survival data
• Biased sampling, over-identified parameter problems and beyond
• Conditional screening for ultra-high dimensional covariates with survival outcomes
• Model-free feature screening for ultrahigh dimensional censored regression
• Quantile-adaptive model-free variable screening for high-dimensional heterogeneous 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
• Simple and fast overidentified rank estimation for right-censored length-biased data and backward recurrence time
• Logistic disease incidence models and case-control studies
• Maximum Likelihood Estimator for Choice-Based Samples
• The Estimation of Choice Probabilities from Choice Based Samples
• Fitting regression models to case-control data by maximum likelihood
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Regression Analysis with Response-selective Sampling
• Sure Independence Screening for Ultrahigh Dimensional Feature Space
• Non-Parametric Tests for Right-Censored Data with Biased Sampling
• Feature Screening via Distance Correlation Learning
• A Unified Approach to Semiparametric Transformation Models Under General Biased Sampling Schemes
• Case-cohort and case-control analysis with Cox's model
• Conditional quantile screening in ultrahigh-dimensional heterogeneous data
• Analyzing Length-Biased Data With Semiparametric Transformation and Accelerated Failure Time Models
• Model-Free Feature Screening for Ultrahigh Dimensional Discriminant Analysis
• The Kolmogorov filter for variable screening in high-dimensional binary classification
• Model Selection and Estimation in Regression with Grouped Variables
• Separate sample logistic discrimination
• Econometrics