biomarkers |
Example biomarker data |
extract_importance_glm |
Extract the learner-specific importance from a glm object |
extract_importance_glmnet |
Extract the learner-specific importance from a glmnet object |
extract_importance_mean |
Extract the learner-specific importance from a mean object |
extract_importance_polymars |
Extract the learner-specific importance from a polymars object |
extract_importance_ranger |
Extract the learner-specific importance from a ranger object |
extract_importance_SL |
Extract extrinsic importance from a Super Learner object |
extract_importance_SL_learner |
Extract the learner-specific importance from a fitted SuperLearner algorithm |
extract_importance_svm |
Extract the learner-specific importance from an svm object |
extract_importance_xgboost |
Extract the learner-specific importance from an xgboost object |
extrinsic_selection |
Perform extrinsic, ensemble-based variable selection |
flevr |
flevr: Flexible, Ensemble-Based Variable Selection with Potentially Missing Data |
get_augmented_set |
Get an augmented set based on the next-most significant variables |
get_base_set |
Get an initial selected set based on intrinsic importance and a base method |
intrinsic_control |
Control parameters for intrinsic variable selection |
intrinsic_selection |
Perform intrinsic, ensemble-based variable selection |
pool_selected_sets |
Pool selected sets from multiply-imputed data |
pool_spvims |
Pool SPVIM Estimates Using Rubin's Rules |
SL.ranger.imp |
Super Learner wrapper for a ranger object with variable importance |
SL_stabs_fitfun |
Wrapper for using Super Learner-based extrinsic selection within stability selection |
spvim_vcov |
Extract a Variance-Covariance Matrix for SPVIM Estimates |