2 papers
math.ST2025
Mathematical Theory of Collinearity Effects on Machine Learning Variable Importance Measures
Kelvyn K. Bladen, D. Richard Cutler, Alan Wisler
In many machine learning problems, understanding variable importance is a central concern. Two common approaches are Permute-and-Predict (PaP), which randomly permutes a feature in…
stat.ML2024
Conditional Local Importance by Quantile Expectations
Kelvyn K. Bladen, Adele Cutler, D. Richard Cutler +1
Global variable importance measures are commonly used to interpret the results of machine learning models. Local variable importance techniques assess how variables contribute to i…