create.data.split {SIAMCAT} | R Documentation

## Split a dataset into training and a test sets.

### Description

This function prepares the cross-validation by splitting the data into `num.folds` training and test folds for `num.resample` times.

### Usage

    create.data.split(siamcat, num.folds = 2, num.resample = 1,
        stratify = TRUE, inseparable = NULL, verbose = 1)

### Arguments

`siamcat` | object of class siamcat-class
`num.folds` | integer number of cross-validation folds (needs to be `>=2`), defaults to `2`
`num.resample` | integer, resampling rounds (values `<= 1` deactivate resampling), defaults to `1`
`stratify` | boolean, should the splits be stratified so that an equal proportion of classes are present in each fold?, defaults to `TRUE`
`inseparable` | string, name of metadata variable to be inseparable, defaults to `NULL`, see Details below
`verbose` | integer, control output: `0` for no output at all, `1` for only information about progress and success, `2` for normal level of information and `3` for full debug information, defaults to `1`

### Details

This function splits the labels within a siamcat-class object and prepares the internal cross-validation for the model training (see train.model).

The function saves the training and test instances for the different cross-validation folds within a list in the `data_split`-slot of the siamcat-class object, which is a list with four entries:

- `num.folds` - the number of cross-validation folds

- `num.resample` - the number of repetitions for the cross-validation

- `training.folds` - a list containing the indices for the training instances

- `test.folds` - a list containing the indices for the test instances

If provided, the data split will take into account a metadata variable for the data split (by providing the `inseparable` argument). For example, if the data contains several samples for the same individual, it would make sense to keep data from the same individual within the same fold. If `inseparable` is given, the `stratify` argument will be ignored.

### Value

object of class siamcat-class with the `data_split`-slot filled

### Examples

    data(siamcat_example)

    # simple working example
    siamcat_split <- create.data.split(siamcat_example,
        num.folds=10,
        num.resample=5,
        stratify=TRUE)

    # Inseparable data split
    ## Not run: siamcat_split <- create.data.split(siamcat,
        num.folds=10,
        num.resample=5,
        inseparable='Individual_ID')
    ## End(Not run)

[Package SIAMCAT version 1.6.0 Index]