PartitioningConfig#

class datarobotx.PartitioningConfig(User=None, Group=None, DateTime=None, validation_type=None, cv_method=None, validation_pct=None, holdout_pct=None, disable_holdout=None, reps=None)#

Partitioning configuration.

Parameters that default to ‘None’ (or are omitted by the user) are overridden to server-side defaults at runtime. Consult the DataRobot REST API and GUI documentation for additional information on each parameter.

Parameters:
  • User (dict or PartitioningUserConfig) – User partitioning configuration

  • Group (dict or PartitioningGroupConfig) – Group partitioning configuration

  • DateTime (dict or PartitioningDateTimeConfig) – Date-time partitioning configuration

  • validation_type ({'CV', 'TVH'}) – The validation method to be used. CV for cross validation or TVH for train-validation-holdout split.

  • cv_method ({'random', 'user', 'stratified', 'group', 'datetime'}) – The partitioning method to be applied to the training data.

  • validation_pct (float) – The percentage of the dataset to assign to the validation set

  • holdout_pct (float) – The percentage of the dataset to assign to the holdout set

  • disable_holdout (bool) – Whether to suppress allocating a holdout fold. If disableHoldout is set to true, holdoutStartDate and holdoutDuration must not be set.

  • reps (int) – The number of cross validation folds to use.

See also

DRConfig

Configuration object for DataRobot project and autopilot settings, also includes detailed examples of usage

Attributes:

cv_method

The partitioning method to be applied to the training data.

DateTime

Date-time partitioning configuration.

disable_holdout

Whether to suppress allocating a holdout fold.

Group

Group partitioning configuration.

holdout_pct

The percentage of the dataset to assign to the holdout set.

reps

The number of cross validation folds to use.

User

User partitioning configuration.

validation_pct

The percentage of the dataset to assign to the validation set.

validation_type

The validation method to be used.

Inherited methods:

keys()

rtype:

Collection[str]

to_dict()

Return configuration as a dict.

property DateTime: PartitioningDateTimeConfig#

Date-time partitioning configuration.

Notes

DateTime : dict or PartitioningDateTimeConfig

property Group: PartitioningGroupConfig#

Group partitioning configuration.

Notes

Group : dict or PartitioningGroupConfig

property User: PartitioningUserConfig#

User partitioning configuration.

Notes

User : dict or PartitioningUserConfig

property cv_method: str#

The partitioning method to be applied to the training data.

Notes

cv_method : {‘random’, ‘user’, ‘stratified’, ‘group’, ‘datetime’}

property disable_holdout: bool#

Whether to suppress allocating a holdout fold. If disableHoldout is set to true, holdoutStartDate and holdoutDuration must not be set.

Notes

disable_holdout : bool

property holdout_pct: float#

The percentage of the dataset to assign to the holdout set.

Notes

holdout_pct : float

property reps: int#

The number of cross validation folds to use.

Notes

reps : int

to_dict()#

Return configuration as a dict.

Return type:

Dict[str, Any]

property validation_pct: float#

The percentage of the dataset to assign to the validation set.

Notes

validation_pct : float

property validation_type: str#

The validation method to be used. CV for cross validation or TVH for train-validation-holdout split.

Notes

validation_type : {‘CV’, ‘TVH’}