Advanced tuning

class datarobot.models.advanced_tuning.AdvancedTuningSession

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.

Variables:

description (str) – 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 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 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_name (str) – Name of the task whose parameter needs to be set

  • parameter_name (str) – Name of the parameter to set

  • parameter_id (str) – ID of the parameter to set

  • value (int, 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”.

Return type:

AdvancedTuningParamsType

Returns:

  • parameters (dict) – “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

  • value (int, float, list, or str) – The current value of the parameter. None if none has been specified.

run()

Submit this model for Advanced Tuning.

Returns:

The created job to build the model

Return type:

datarobot.models.modeljob.ModelJob