rsample (version 1.1.0)

group_mc_cv: Group Monte Carlo Cross-Validation

Description

Group Monte Carlo cross-validation creates splits of the data based on some grouping variable (which may have more than a single row associated with it). One resample of Monte Carlo cross-validation takes a random sample (without replacement) of groups in the original data set to be used for analysis. All other data points are added to the assessment set. A common use of this kind of resampling is when you have repeated measures of the same subject.

Usage

group_mc_cv(data, group, prop = 3/4, times = 25, ...)

Value

A tibble with classes group_mc_cv, rset, tbl_df, tbl, and data.frame. The results include a column for the data split objects and an identification variable.

Arguments

data

A data frame.

group

A variable in data (single character or name) used for grouping observations with the same value to either the analysis or assessment set within a fold.

prop

The proportion of data to be retained for modeling/analysis.

times

The number of times to repeat the sampling.

...

Not currently used.

Examples

data(ames, package = "modeldata")

set.seed(123)
group_mc_cv(ames, group = Neighborhood, times = 5)