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# rsample <a href='https://rsample.tidymodels.org/'><img src='man/figures/logo.png' align="right" height="139" alt="a boot on a green background" /></a>
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## Overview
The rsample package provides functions to create different types of
resamples and corresponding classes for their analysis. The goal is to
have a modular set of methods that can be used for:
- resampling for estimating the sampling distribution of a statistic
- estimating model performance using a holdout set
The scope of rsample is to provide the basic building blocks for
creating and analyzing resamples of a data set, but this package does
not include code for modeling or calculating statistics. The [Working
with Resample
Sets](https://rsample.tidymodels.org/articles/Working_with_rsets.html)
vignette gives a demonstration of how rsample tools can be used when
building models.
Note that resampled data sets created by rsample are directly accessible
in a resampling object but do not contain much overhead in memory. Since
the original data is not modified, R does not make an automatic copy.
For example, creating 50 bootstraps of a data set does not create an
object that is 50-fold larger in memory:
``` r
library(rsample)
library(mlbench)
data(LetterRecognition)
lobstr::obj_size(LetterRecognition)
#> 2,644,640 B
set.seed(35222)
boots <- bootstraps(LetterRecognition, times = 50)
lobstr::obj_size(boots)
#> 6,686,776 B
# Object size per resample
lobstr::obj_size(boots)/nrow(boots)
#> 133,735.5 B
# Fold increase is <<< 50
as.numeric(lobstr::obj_size(boots)/lobstr::obj_size(LetterRecognition))
#> [1] 2.528426
```
<sup>Created on 2022-02-28 by the [reprex
package](https://reprex.tidyverse.org) (v2.0.1)</sup>
The memory usage for 50 bootstrap samples is less than 3-fold more than
the original data set.
## Installation
To install it, use:
``` r
install.packages("rsample")
```
And the development version from [GitHub](https://github.com/) with:
``` r
# install.packages("pak")
pak::pak("rsample")
```
## Contributing
This project is released with a [Contributor Code of
Conduct](https://contributor-covenant.org/version/2/1/CODE_OF_CONDUCT.html).
By contributing to this project, you agree to abide by its terms.
- For questions and discussions about tidymodels packages, modeling, and
machine learning, please [post on Posit
Community](https://forum.posit.co/new-topic?category_id=15&tags=tidymodels,question).
- If you think you have encountered a bug, please [submit an
issue](https://github.com/tidymodels/rsample/issues).
- Either way, learn how to create and share a
[reprex](https://reprex.tidyverse.org/articles/articles/learn-reprex.html)
(a minimal, reproducible example), to clearly communicate about your
code.
- Check out further details on [contributing guidelines for tidymodels
packages](https://www.tidymodels.org/contribute/) and [how to get
help](https://www.tidymodels.org/help/).
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