keep_groups_in_cv_partitions: Whether groups can be kept together in partitions during...

Description Usage Arguments Value Author(s)

View source: R/cross_val.R

Description

Whether groups can be kept together in partitions during cross-validation

Usage

1
keep_groups_in_cv_partitions(groups, group_partitions, kfold)

Arguments

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.

kfold

Fold number for k-fold cross-validation (default: 5).

Value

TRUE if possible, FALSE otherwise

Author(s)

Kelly Sovacool, sovacool@umich.edu


SchlossLab/mikropml documentation built on Nov. 25, 2021, 1:13 p.m.