ROC curve

class datarobot.models.roc_curve.RocCurve

ROC curve data for model.

Variables:

  • source (str) – ROC curve data source. Can be ‘validation’, ‘crossValidation’ or ‘holdout’.

  • roc_points (list of dict) – List of precalculated metrics associated with thresholds for ROC curve.

  • negative_class_predictions (list of float) – List of predictions from example for negative class

  • positive_class_predictions (list of float) – List of predictions from example for positive class

  • source_model_id (str) – ID of the model this ROC curve represents; in some cases, insights from the parent of a frozen model may be used

  • data_slice_id (str) – ID of the data slice this ROC curve represents.

classmethod from_server_data(data, keep_attrs=None, use_insights_format=False, **kwargs)

Overwrite APIObject.from_server_data to handle roc curve data retrieved from either legacy URL or /insights/ new URL.

Parameters:

  • data (dict) – The directly translated dict of JSON from the server. No casing fixes have taken place.

  • keep_attrs (iterable) – List, set or tuple of the dotted namespace notations for attributes to keep within the object structure even if their values are None

  • use_insights_format (Optional[bool]) – Whether to repack the data from the format used in the GET /insights/RocCur/ URL to the format used in the legacy URL.

Return type:

RocCurve

class datarobot.models.roc_curve.LabelwiseRocCurve

Labelwise ROC curve data for one label and one source.

Variables:

  • source (str) – ROC curve data source. Can be ‘validation’, ‘crossValidation’ or ‘holdout’.

  • roc_points (list of dict) – List of precalculated metrics associated with thresholds for ROC curve.

  • negative_class_predictions (list of float) – List of predictions from example for negative class

  • positive_class_predictions (list of float) – List of predictions from example for positive class

  • source_model_id (str) – ID of the model this ROC curve represents; in some cases, insights from the parent of a frozen model may be used

  • label (str) – Label name for

  • kolmogorov_smirnov_metric (float) – Kolmogorov-Smirnov metric value for label

  • auc (float) – AUC metric value for label