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Found 3 papers, 3 papers with code
Practical considerations for variable screening in the Super Learner
However, the performance of a Super Learner using the lasso for dimension reduction has not been fully explored in cases where the lasso is known to perform poorly.
Efficient nonparametric statistical inference on population feature importance using Shapley values
The true population-level importance of a variable in a prediction task provides useful knowledge about the underlying data-generating mechanism and can help in deciding which measurements to collect in subsequent experiments.
A general framework for inference on algorithm-agnostic variable importance
In many applications, it is of interest to assess the relative contribution of features (or subsets of features) toward the goal of predicting a response -- in other words, to gauge the variable importance of features.
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