Copyright | (c) 2013-2023 Brendan Hay |
---|---|
License | Mozilla Public License, v. 2.0. |
Maintainer | Brendan Hay |
Stability | auto-generated |
Portability | non-portable (GHC extensions) |
Safe Haskell | Safe-Inferred |
Language | Haskell2010 |
Documentation
data AutoMLDataSplitConfig Source #
This structure specifies how to split the data into train and validation datasets. The validation and training datasets must contain the same headers. The validation dataset must be less than 2 GB in size.
See: newAutoMLDataSplitConfig
smart constructor.
AutoMLDataSplitConfig' | |
|
Instances
newAutoMLDataSplitConfig :: AutoMLDataSplitConfig Source #
Create a value of AutoMLDataSplitConfig
with all optional fields omitted.
Use generic-lens or optics to modify other optional fields.
The following record fields are available, with the corresponding lenses provided for backwards compatibility:
$sel:validationFraction:AutoMLDataSplitConfig'
, autoMLDataSplitConfig_validationFraction
- The validation fraction (optional) is a float that specifies the portion
of the training dataset to be used for validation. The default value is
0.2, and values must be greater than 0 and less than 1. We recommend
setting this value to be less than 0.5.
autoMLDataSplitConfig_validationFraction :: Lens' AutoMLDataSplitConfig (Maybe Double) Source #
The validation fraction (optional) is a float that specifies the portion of the training dataset to be used for validation. The default value is 0.2, and values must be greater than 0 and less than 1. We recommend setting this value to be less than 0.5.