In this paper, we introduce a unified and robust model-free feature screening approach for high-dimensional survival data with censoring, which has several advantages: it is a model-free approach under a general model framework, and hence avoids the complication to specify an actual model form ...
Model-free feature screening via distance correlation for ultrahigh dimensional survival dataDistance correlationModel-free screeningSure screening propertySurvival dataUltrahigh dimensional dataWith the explosion of ultrahigh dimensional data in various fields, many sure independent screening methods have been ...
In this paper we design a sure independent ranking and screening procedure for censored regression (cSIRS, for short) with ultrahigh dimensional covariates. The inverse probability weighted cSIRS procedure is model-free in the sense that it does not specify a parametric or semiparametric regression f...
Model-Free Feature Screening for Ultrahigh Dimensional Discriminant Analysis This work is concerned with marginal sure independence feature screening for ultrahigh dimensional discriminant analysis. The response variable is categori... H Cui,R Li,W Zhong - 《Journal of the American Statistical Association...
Feature Screening%Pearson’s Chi-Square Test%Screening Consistency%Search Engine Marketing%Text Classification%Ultrahigh Dimensional Data Ultrahigh dimensional data with both categorical responses and categorical covariates are frequently encountered in the analysis of big data, for which fea... Danyang,Huang...
The feature screening procedure based on the expected conditional Kolmogorov filter is proposed for the ultrahigh dimensional binary classification problem with dependent variable. The sure screening and ranking consistency properties are established. Some numerical examples are also presented....
(a) It is model-free in that its implementation does not require a specification on the model structure; (b) it is robust to heavy-tailed distributions or outliers in both directions of response and predictors; and (c) it can deal with both feature screening and the conditional screening ...
which avoids the specification of a particular model structure. Second, it is condition-free, which does not require any extra conditions except for some regularity conditions for high-dimensional feature screening. The numerical results indicate that, compared to the existing methods, the proposed met...
The sure screening property is proven for both methods. It is shown that the complete case analysis can also keep the sure screening property of any feature screening approach with sure screening property. 展开 关键词: borrowing missingness information missing data ultrahigh dimensionality variable ...
Model-free feature screening for ultrahigh-dimensional data conditional on some variables In this paper, the conditional distance correlation (CDC) is used as a measure of correlation to develop a conditional feature screening procedure given so... Y Liu,Q Wang - 《Annals of the Institute of Sta...