Advanced Tuning
- class datarobot.models.advanced_tuning.AdvancedTuningSession(model)
A session enabling users to configure and run advanced tuning for a model.
Every model contains a set of one or more tasks. Every task contains a set of zero or more parameters. This class allows tuning the values of each parameter on each task of a model, before running that model.
This session is client-side only and is not persistent. Only the final model, constructed when run is called, is persisted on the DataRobot server.
- Attributes:
- descriptionstr
Description for the new advance-tuned model. Defaults to the same description as the base model.
- get_task_names()
Get the list of task names that are available for this model
- Returns:
- list(str)
List of task names
- Return type:
List[str]
- get_parameter_names(task_name)
Get the list of parameter names available for a specific task
- Returns:
- list(str)
List of parameter names
- Return type:
List[str]
- set_parameter(value, task_name=None, parameter_name=None, parameter_id=None)
Set the value of a parameter to be used
The caller must supply enough of the optional arguments to this function to uniquely identify the parameter that is being set. For example, a less-common parameter name such as ‘building_block__complementary_error_function’ might only be used once (if at all) by a single task in a model. In which case it may be sufficient to simply specify ‘parameter_name’. But a more-common name such as ‘random_seed’ might be used by several of the model’s tasks, and it may be necessary to also specify ‘task_name’ to clarify which task’s random seed is to be set. This function only affects client-side state. It will not check that the new parameter value(s) are valid.
- Parameters:
- task_namestr
Name of the task whose parameter needs to be set
- parameter_namestr
Name of the parameter to set
- parameter_idstr
ID of the parameter to set
- valueint, float, list, or str
New value for the parameter, with legal values determined by the parameter being set
- Raises:
- NoParametersFoundException
if no matching parameters are found.
- NonUniqueParametersException
if multiple parameters matched the specified filtering criteria
- Return type:
None
- get_parameters()
Returns the set of parameters available to this model
The returned parameters have one additional key, “value”, reflecting any new values that have been set in this AdvancedTuningSession. When the session is run, “value” will be used, or if it is unset, “current_value”.
- Returns:
- parametersdict
“Parameters” dictionary, same as specified on Model.get_advanced_tuning_params.
- An additional field is added per parameter to the ‘tuning_parameters’ list in the dictionary:
- valueint, float, list, or str
The current value of the parameter. None if none has been specified.
- Return type: