Advanced Options API¶
AdvancedOptions(weights=None, response_cap=None, blueprint_threshold=None, seed=None, smart_downsampled=False, majority_downsampling_rate=None, offset=None, exposure=None, accuracy_optimized_mb=None, scaleout_modeling_mode=None, events_count=None, monotonic_increasing_featurelist_id=None, monotonic_decreasing_featurelist_id=None, only_include_monotonic_blueprints=None)¶
Used when setting the target of a project to set advanced options of modeling process.
weights : string, optional
The name of a column indicating the weight of each row
response_cap : float in [0.5, 1), optional
Quantile of the response distribution to use for response capping.
blueprint_threshold : int, optional
Number of hours models are permitted to run before being excluded from later autopilot stages Minimum 1
seed : int
a seed to use for randomization
smart_downsampled : bool
whether to use smart downsampling to throw away excess rows of the majority class. Only applicable to classification and zero-boosted regression projects.
majority_downsampling_rate : float
the percentage between 0 and 100 of the majority rows that should be kept. Specify only if using smart downsampling. May not cause the majority class to become smaller than the minority class.
offset : list of str, optional
(New in version v2.6) the list of the names of the columns containing the offset of each row
exposure : string, optional
(New in version v2.6) the name of a column containing the exposure of each row
accuracy_optimized_mb : bool, optional
(New in version v2.6) Include additional, longer-running models that will be run by the autopilot and available to run manually.
scaleout_modeling_mode : string, optional
(New in version v2.8) Specifies the behavior of Scaleout models for the project. This is one of
datarobot.enums.SCALEOUT_MODELING_MODE.DISABLED, no models will run during autopilot or show in the list of available blueprints. Scaleout models must be disabled for some partitioning settings including projects using datetime partitioning or projects using offset or exposure columns. If
datarobot.enums.SCALEOUT_MODELING_MODE.REPOSITORY_ONLY, scaleout models will be in the list of available blueprints but not run during autopilot. If
datarobot.enums.SCALEOUT_MODELING_MODE.AUTOPILOT, scaleout models will run during autopilot and be in the list of available blueprints. Scaleout models are only supported in the Hadoop enviroment with the corresponding user permission set.
events_count : string, optional
(New in version v2.8) the name of a column specifying events count.
monotonic_increasing_featurelist_id : string, optional
(new in version 2.11) the id of the featurelist that defines the set of features with a monotonically increasing relationship to the target. If None, no such constraints are enforced. When specified, this will set a default for the project that can be overriden at model submission time if desired.
monotonic_decreasing_featurelist_id : string, optional
(new in version 2.11) the id of the featurelist that defines the set of features with a monotonically decreasing relationship to the target. If None, no such constraints are enforced. When specified, this will set a default for the project that can be overriden at model submission time if desired.
only_include_monotonic_blueprints : bool, optional
(new in version 2.11) when true, only blueprints that support enforcing monotonic constraints will be available in the project or selected for the autopilot.
import datarobot as dr advanced_options = dr.AdvancedOptions( weights='weights_column', offset=['offset_column'], exposure='exposure_column', response_cap=0.7, blueprint_threshold=2, smart_downsampled=True, majority_downsampling_rate=75.0)