Innovated interaction screening for high-dimensional nonlinear classification

DOI10.1214/14-AOS1308zbMath1328.62383arXiv1501.01029OpenAlexW2763089461MaRDI QIDQ2352740

Zemin Zheng, Yingying Fan, Yinfei Kong, Daoji Li

Publication date: 6 July 2015

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1501.01029

zbMATH Keywords

classificationdiscriminant analysisdimension reductionsparsitysure screening propertyinteraction screening

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Generalized linear models (logistic models) (62J12) Asymptotic properties of parametric tests (62F05)

Related Items

Interaction identification and clique screening for classification with ultra-high dimensional discrete features, Scalable inference for high-dimensional precision matrix, Variance ratio screening for ultrahigh dimensional discriminant analysis, A \(U\)-classifier for high-dimensional data under non-normality, BOLT-SSI: A Statistical Approach to Screening Interaction Effects for Ultra-High Dimensional Data, Threshold Selection in Feature Screening for Error Rate Control, Sparse and Low-Rank Matrix Quantile Estimation With Application to Quadratic Regression, Scalable and efficient inference via CPE, Unified model-free interaction screening via CV-entropy filter, Unnamed Item, The Kendall interaction filter for variable interaction screening in high dimensional classification problems, A Simple Two-Sample Test in High Dimensions Based on L²-Norm, RANK: Large-Scale Inference With Graphical Nonlinear Knockoffs, Greedy forward regression for variable screening, Penalized Interaction Estimation for Ultrahigh Dimensional Quadratic Regression, Unnamed Item, Screening and selection for quantile regression using an alternative measure of variable importance, Unnamed Item, Model Selection for High-Dimensional Quadratic Regression via Regularization, Dynamic linear discriminant analysis in high dimensional space, Robust Variable and Interaction Selection for Logistic Regression and General Index Models, Reproducible learning in large-scale graphical models, Intentional Control of Type I Error Over Unconscious Data Distortion: A Neyman–Pearson Approach to Text Classification, Innovated interaction screening for high-dimensional nonlinear classification

Uses Software

• glasso
• glmnet

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