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Found 4 papers, 1 papers with code
Analysis of ensemble feature selection for correlated high-dimensional RNA-Seq cancer data
Unfortunately, models built on feature sets obtained from the ensemble of feature selection algorithms were no better than for models developed on feature sets obtained from individual algorithms.
Bootstrap Bias Corrected Cross Validation applied to Super Learning
The default method for verification of super learner results is by nested cross validation.
All-relevant feature selection using multidimensional filters with exhaustive search
This paper describes a method for identification of the informative variables in the information system with discrete decision variables.
Feature Selection with the Boruta Package
This article describes a R package Boruta, implementing a novel feature selection algorithm for finding all relevant variables.
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