Frozen Model API

class datarobot.models.FrozenModel(id=None, processes=None, featurelist_name=None, featurelist_id=None, project_id=None, sample_pct=None, training_row_count=None, training_duration=None, training_start_date=None, training_end_date=None, model_type=None, model_category=None, is_frozen=None, blueprint_id=None, metrics=None, parent_model_id=None, monotonic_increasing_featurelist_id=None, monotonic_decreasing_featurelist_id=None, supports_monotonic_constraints=None, is_starred=None, prediction_threshold=None, prediction_threshold_read_only=None)

A model tuned with parameters which are derived from another model

Attributes

id (str) the id of the model
project_id (str) the id of the project the model belongs to
processes (list of str) the processes used by the model
featurelist_name (str) the name of the featurelist used by the model
featurelist_id (str) the id of the featurelist used by the model
sample_pct (float) the percentage of the project dataset used in training the model
training_row_count (int or None) the number of rows of the project dataset used in training the model. In a datetime partitioned project, if specified, defines the number of rows used to train the model and evaluate backtest scores; if unspecified, either training_duration or training_start_date and training_end_date was used to determine that instead.
training_duration (str or None) only present for models in datetime partitioned projects. If specified, a duration string specifying the duration spanned by the data used to train the model and evaluate backtest scores.
training_start_date (datetime or None) only present for frozen models in datetime partitioned projects. If specified, the start date of the data used to train the model.
training_end_date (datetime or None) only present for frozen models in datetime partitioned projects. If specified, the end date of the data used to train the model.
model_type (str) what model this is, e.g. ‘Nystroem Kernel SVM Regressor’
model_category (str) what kind of model this is - ‘prime’ for DataRobot Prime models, ‘blend’ for blender models, and ‘model’ for other models
is_frozen (bool) whether this model is a frozen model
parent_model_id (str) the id of the model that tuning parameters are derived from
blueprint_id (str) the id of the blueprint used in this model
metrics (dict) a mapping from each metric to the model’s scores for that metric
monotonic_increasing_featurelist_id (str) optional, 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.
monotonic_decreasing_featurelist_id (str) optional, 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.
supports_monotonic_constraints (bool) optional, whether this model supports enforcing monotonic constraints
is_starred (bool) whether this model marked as starred
prediction_threshold (float) for binary classification projects, the threshold used for predictions
prediction_threshold_read_only (bool) indicated whether modification of the prediction threshold is forbidden. Threshold modification is forbidden once a model has had a deployment created or predictions made via the dedicated prediction API.
classmethod get(project_id, model_id)

Retrieve a specific frozen model.

Parameters:

project_id : str

The project’s id.

model_id : str

The model_id of the leaderboard item to retrieve.

Returns:

model : FrozenModel

The queried instance.