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rsample (version 0.1.1)
General Resampling Infrastructure
Description
Classes and functions to create and summarize different types of resampling objects (e.g. bootstrap, cross-validation).
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Install
install.packages('rsample')
Monthly Downloads
64,989
Version
0.1.1
License
MIT + file LICENSE
Issues
27
Pull Requests
1
Stars
323
Forks
57
Repository
https://github.com/tidymodels/rsample
Homepage
https://rsample.tidymodels.org
Maintainer
Julia Silge
Last Published
November 8th, 2021
Functions in rsample (0.1.1)
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bootstraps
Bootstrap Sampling
.get_fingerprint
Obtain a identifier for the resamples
add_resample_id
Augment a data set with resampling identifiers
drinks
Sample Time Series Data
complement
Determine the Assessment Samples
as.data.frame.rsplit
Convert an
rsplit
object to a data frame
form_pred
Extract Predictor Names from Formula or Terms
gather.rset
Gather an
rset
Object
apparent
Sampling for the Apparent Error Rate
int_pctl
Bootstrap confidence intervals
manual_rset
Manual resampling
pretty.vfold_cv
Short Descriptions of rsets
rsample2caret
Convert Resampling Objects to Other Formats
reexports
Objects exported from other packages
nested_cv
Nested or Double Resampling
new_rset
Constructor for new rset objects
labels.rset
Find Labels from rset Object
permutations
Permutation sampling
mc_cv
Monte Carlo Cross-Validation
populate
Add Assessment Indices
rset_reconstruct
Extending rsample with new rset subclasses
attrition
Job Attrition
make_strata
Create or Modify Stratification Variables
make_splits
Constructors for split objects
labels.rsplit
Find Labels from rsplit Object
group_vfold_cv
Group V-Fold Cross-Validation
initial_split
Simple Training/Test Set Splitting
loo_cv
Leave-One-Out Cross-Validation
rsample-dplyr
Compatibility with dplyr
rsample
rsample: General Resampling Infrastructure for R
vfold_cv
V-Fold Cross-Validation
tidy.rsplit
Tidy Resampling Object
slide-resampling
Time-based Resampling
rolling_origin
Rolling Origin Forecast Resampling
reg_intervals
A convenience function for confidence intervals with linear-ish parametric models
two_class_dat
Two Class Data
validation_split
Create a Validation Set