:py:mod:`abacusai.prediction_metric`
====================================

.. py:module:: abacusai.prediction_metric


Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   abacusai.prediction_metric.PredictionMetric




.. py:class:: PredictionMetric(client, createdAt=None, featureGroupId=None, predictionMetricConfig=None, predictionMetricId=None, modelMonitorId=None, projectId=None, refreshSchedules={}, latestPredictionMetricVersionDescription={})

   Bases: :py:obj:`abacusai.return_class.AbstractApiClass`

   A Prediction Metric job description.

   :param client: An authenticated API Client instance
   :type client: ApiClient
   :param createdAt: Date and time when this prediction metric was created.
   :type createdAt: str
   :param featureGroupId: The feature group used as input to this prediction metric.
   :type featureGroupId: str
   :param predictionMetricConfig: Specification for the prediction metric to run in this job.
   :type predictionMetricConfig: json
   :param predictionMetricId: The unique identifier of the prediction metric.
   :type predictionMetricId: str
   :param modelMonitorId: unique string identifier for model monitor that created prediction metric
   :type modelMonitorId: str
   :param projectId: The project this prediction metric belongs to.
   :type projectId: str
   :param latestPredictionMetricVersionDescription: Description of the latest prediction metric version (if any).
   :type latestPredictionMetricVersionDescription: PredictionMetricVersion
   :param refreshSchedules: List of schedules that determines when the next version of the dataset will be created.
   :type refreshSchedules: RefreshSchedule

   .. py:method:: __repr__()

      Return repr(self).


   .. py:method:: to_dict()

      Get a dict representation of the parameters in this class

      :returns: The dict value representation of the class parameters
      :rtype: dict


   .. py:method:: refresh()

      Calls describe and refreshes the current object's fields

      :returns: The current object
      :rtype: PredictionMetric


   .. py:method:: describe(should_include_latest_version_description = True)

      Describe a Prediction Metric.

      :param should_include_latest_version_description: include the description of the latest prediction metric version
      :type should_include_latest_version_description: bool

      :returns: The prediction metric object.
      :rtype: PredictionMetric


   .. py:method:: delete()

      Removes an existing PredictionMetric.

      :param prediction_metric_id: The unique ID associated with the prediction metric.
      :type prediction_metric_id: str


   .. py:method:: run()

      Creates a new prediction metrics job run for the given prediction metric job description, and starts that job.

      Configures and starts the computations running to compute the prediciton metric.


      :param prediction_metric_id: The prediction metric job description to apply for configuring a prediction metric job.
      :type prediction_metric_id: str

      :returns: A prediction metric version. For more information, please refer to the details on the object (below).
      :rtype: PredictionMetricVersion


   .. py:method:: list_versions(limit = 100, start_after_id = None)

      List the prediction metric versions for a prediction metric.

      :param limit: The the number of prediction metric instances to be retrieved.
      :type limit: int
      :param start_after_id: An offset parameter to exclude all prediction metric versions till the specified prediction metric ID.
      :type start_after_id: str

      :returns: The prediction metric instances for this prediction metric.
      :rtype: PredictionMetricVersion



