CreateRandomPartition: Create a random sampling-based S3 object of class partition...

In datarobot: 'DataRobot' Predictive Modeling API

Create a random sampling-based S3 object of class partition for the SetTarget function

Description

Random partitioning is supported for either Training/Validation/Holdout ("TVH") or cross-validation ("CV") splits. In either case, the holdout percentage (holdoutPct) must be specified; for the "CV" method, the number of cross-validation folds (reps) must also be specified, while for the "TVH" method, the validation subset percentage (validationPct) must be specified.

Usage

CreateRandomPartition(
  validationType,
  holdoutPct,
  reps = NULL,
  validationPct = NULL
)

Arguments

validationType	character. String specifying the type of partition generated, either "TVH" or "CV".
holdoutPct	integer. The percentage of data to be used as the holdout subset.
reps	integer. The number of cross-validation folds to generate; only applicable when validationType = "CV".
validationPct	integer. The percentage of data to be used as the validation subset.

Details

This function is one of several convenience functions provided to simplify the task of starting modeling projects with custom partitioning options. The other functions are CreateGroupPartition, CreateStratifiedPartition, and CreateUserPartition.

Value

An S3 object of class partition including the parameters required by SetTarget to generate a random partitioning of the modeling dataset.

See Also

CreateStratifiedPartition, CreateGroupPartition, CreateUserPartition.

Examples

CreateRandomPartition(validationType = "CV", holdoutPct = 20, reps = 5)

datarobot documentation built on May 29, 2024, 4:36 a.m.