Package index • rsample

Resampling methods

initial_split() initial_time_split() training() testing() group_initial_split(): Simple Training/Test Set Splitting

initial_validation_split() initial_validation_time_split() group_initial_validation_split() training(<initial_validation_split>) testing(<initial_validation_split>) validation(): Create an Initial Train/Validation/Test Split

validation_set() analysis(<val_split>) assessment(<val_split>) training(<val_split>) validation(<val_split>) testing(<val_split>): Create a Validation Split for Tuning

bootstraps(): Bootstrap Sampling

group_bootstraps(): Group Bootstraps

vfold_cv(): V-Fold Cross-Validation

group_vfold_cv(): Group V-Fold Cross-Validation

mc_cv(): Monte Carlo Cross-Validation

group_mc_cv(): Group Monte Carlo Cross-Validation

clustering_cv(): Cluster Cross-Validation

nested_cv(): Nested or Double Resampling

loo_cv(): Leave-One-Out Cross-Validation

rolling_origin() superseded: Rolling Origin Forecast Resampling

sliding_window() sliding_index() sliding_period(): Time-based Resampling

apparent(): Sampling for the Apparent Error Rate

permutations(): Permutation sampling

manual_rset(): Manual resampling

Analysis

int_pctl() int_t() int_bca(): Bootstrap confidence intervals

reg_intervals(): A convenience function for confidence intervals with linear-ish parametric models

Utilities

.get_fingerprint(): Obtain a identifier for the resamples

as.data.frame(<rsplit>) analysis() assessment(): Convert an rsplit object to a data frame

add_resample_id(): Augment a data set with resampling identifiers

complement(): Determine the Assessment Samples

form_pred(): Extract Predictor Names from Formula or Terms

get_rsplit(): Retrieve individual rsplits objects from an rset

labels(<rset>) labels(<vfold_cv>): Find Labels from rset Object

labels(<rsplit>): Find Labels from rsplit Object

make_splits(): Constructors for split objects

make_strata(): Create or Modify Stratification Variables

populate(): Add Assessment Indices

reshuffle_rset(): "Reshuffle" an rset to re-generate a new rset with the same parameters

reverse_splits(): Reverse the analysis and assessment sets

rsample2caret() caret2rsample(): Convert Resampling Objects to Other Formats

rset_reconstruct(): Extending rsample with new rset subclasses

tidy(<rsplit>) tidy(<rset>) tidy(<vfold_cv>) tidy(<nested_cv>): Tidy Resampling Object

Compatibility

rsample-dplyr: Compatibility with dplyr