:py:mod:`abacusai.feature_drift_summary`
========================================

.. py:module:: abacusai.feature_drift_summary


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

Classes
~~~~~~~

.. autoapisummary::

   abacusai.feature_drift_summary.FeatureDriftSummary




.. py:class:: FeatureDriftSummary(client, featureIndex=None, name=None, distance=None, jsDistance=None, wsDistance=None, ksStatistic=None, predictionDrift=None, targetColumn=None, dataIntegrityTimeseries=None, nestedSummary=None, nullViolations={}, typeViolations={}, rangeViolations={}, catViolations={})

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

   Summary of important model monitoring statistics for features available in a model monitoring instance

   :param client: An authenticated API Client instance
   :type client: ApiClient
   :param featureIndex: A list of dicts of eligible feature names and corresponding overall feature drift measures.
   :type featureIndex: list[dict]
   :param name: Name of feature.
   :type name: str
   :param distance: Symmetric sum of KL divergences between the training distribution and the range of values in the specified window.
   :type distance: float
   :param jsDistance: JS divergence between the training distribution and the range of values in the specified window.
   :type jsDistance: float
   :param wsDistance: Wasserstein distance between the training distribution and the range of values in the specified window.
   :type wsDistance: float
   :param ksStatistic: Kolmogorov-Smirnov statistic computed between the training distribution and the range of values in the specified window.
   :type ksStatistic: float
   :param predictionDrift: Drift for the target column.
   :type predictionDrift: float
   :param targetColumn: Target column name.
   :type targetColumn: str
   :param dataIntegrityTimeseries: Frequency vs Data Integrity Violation Charts.
   :type dataIntegrityTimeseries: dict
   :param nestedSummary: Summary of model monitoring statistics for nested features.
   :type nestedSummary: list[dict]
   :param nullViolations: A list of dicts of feature names and a description of corresponding null violations.
   :type nullViolations: NullViolation
   :param typeViolations: A list of dicts of feature names and corresponding type mismatches.
   :type typeViolations: TypeViolation
   :param rangeViolations: A list of dicts of numerical feature names and corresponding prediction range discrepancies.
   :type rangeViolations: RangeViolation
   :param catViolations: A list of dicts of categorical feature names and corresponding prediction range discrepancies.
   :type catViolations: CategoricalRangeViolation

   .. 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



