check_group_partitions: Check the validity of the group_partitions list

In mikropml: User-Friendly R Package for Supervised Machine Learning Pipelines

Check the validity of the group_partitions list

Description

Check the validity of the group_partitions list

Usage

check_group_partitions(dataset, groups, group_partitions)

Arguments

dataset	Data frame with an outcome variable and other columns as features.
groups	Vector of groups to keep together when splitting the data into train and test sets. If the number of groups in the training set is larger than kfold, the groups will also be kept together for cross-validation. Length matches the number of rows in the dataset (default: NULL).
group_partitions	Specify how to assign groups to the training and testing partitions (default: NULL). If groups specifies that some samples belong to group "A" and some belong to group "B", then setting group_partitions = list(train = c("A", "B"), test = c("B")) will result in all samples from group "A" being placed in the training set, some samples from "B" also in the training set, and the remaining samples from "B" in the testing set. The partition sizes will be as close to training_frac as possible. If the number of groups in the training set is larger than kfold, the groups will also be kept together for cross-validation.

Author(s)

Kelly Sovacool, [e-mail]

Examples

## Not run: 
check_group_partitions(
  otu_mini_bin,
  sample(LETTERS[1:8],
    size = nrow(otu_mini_bin),
    replace = TRUE
  ),
  list(train = c("A", "B"), test = c("C", "D"))
)

## End(Not run)

mikropml documentation built on Aug. 21, 2023, 5:10 p.m.