Perform Inference on Algorithm-Agnostic Variable Importance

[Up] [Top]

Documentation for package ‘vimp’ version 2.1.9

Help Pages

average_vim Average multiple independent importance estimates
cv_vim Nonparametric Intrinsic Variable Importance Estimates and Inference using Cross-fitting
est_predictiveness Estimate a nonparametric predictiveness functional
est_predictiveness_cv Estimate a nonparametric predictiveness functional using cross-validation
format.vim Format a 'vim' object
measure_accuracy Estimate the classification accuracy
measure_anova Estimate ANOVA decomposition-based variable importance.
measure_auc Estimate area under the receiver operating characteristic curve (AUC)
measure_cross_entropy Estimate the cross-entropy
measure_deviance Estimate the deviance
measure_mse Estimate mean squared error
measure_r_squared Estimate R-squared
merge_vim Merge multiple 'vim' objects into one
print.vim Print a 'vim' object
sample_subsets Create necessary objects for SPVIMs
spvim_ics Influence function estimates for SPVIMs
spvim_se Standard error estimate for SPVIM values
sp_vim Shapley Population Variable Importance Measure (SPVIM) Estimates and Inference
vim Nonparametric Intrinsic Variable Importance Estimates and Inference
vimp vimp: Perform Inference on Algorithm-Agnostic Intrinsic Variable Importance
vimp_accuracy Nonparametric Intrinsic Variable Importance Estimates: Classification accuracy
vimp_anova Nonparametric Intrinsic Variable Importance Estimates: ANOVA
vimp_auc Nonparametric Intrinsic Variable Importance Estimates: AUC
vimp_ci Confidence intervals for variable importance
vimp_deviance Nonparametric Intrinsic Variable Importance Estimates: Deviance
vimp_hypothesis_test Perform a hypothesis test against the null hypothesis of delta importance
vimp_regression Nonparametric Intrinsic Variable Importance Estimates: ANOVA
vimp_rsquared Nonparametric Intrinsic Variable Importance Estimates: R-squared
vimp_se Estimate standard errors