:py:mod:`rhino_health.lib.metrics.classification`
=================================================

.. py:module:: rhino_health.lib.metrics.classification


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

Classes
~~~~~~~

.. autoapisummary::

   rhino_health.lib.metrics.classification.AccuracyScore
   rhino_health.lib.metrics.classification.AveragePrecisionScore
   rhino_health.lib.metrics.classification.BalancedAccuracyScore
   rhino_health.lib.metrics.classification.BrierScoreLoss
   rhino_health.lib.metrics.classification.CohenKappaScore
   rhino_health.lib.metrics.classification.ConfusionMatrix
   rhino_health.lib.metrics.classification.DCGScore
   rhino_health.lib.metrics.classification.F1Score
   rhino_health.lib.metrics.classification.FBetaScore
   rhino_health.lib.metrics.classification.HammingLossMetric
   rhino_health.lib.metrics.classification.HingeLossMetric
   rhino_health.lib.metrics.classification.JaccardScore
   rhino_health.lib.metrics.classification.LogLoss
   rhino_health.lib.metrics.classification.MatthewsCorrelationCoefficient
   rhino_health.lib.metrics.classification.NDCGScore
   rhino_health.lib.metrics.classification.PrecisionScore
   rhino_health.lib.metrics.classification.RecallScore
   rhino_health.lib.metrics.classification.TopKAccuracyScore
   rhino_health.lib.metrics.classification.ZeroOneLoss




.. py:class:: AccuracyScore(**data: Any)


   Bases: :py:obj:`rhino_health.lib.metrics.base_metric.AggregatableMetric`

   
   Calculates the `Accuracy Score <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.accuracy_score.html#sklearn.metrics.accuracy_score>`_













   .. rubric:: Examples

   >>> accuracy_score_configuration = AccuracyScore(
   ...   y_true = 'first_binary_column',
   ...   y_pred = 'second_binary_column',
   ...   normalize = False,
   ...   sample_weight = [ 0.1, 0.2, 1, 0, ..... ],
   ... )
   >>> my_dataset.get_metric(accuracy_score_configuration)



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   .. py:attribute:: y_true
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: y_pred
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: normalize
      :type: Optional[bool]
      :value: True

      

   .. py:attribute:: sample_weight
      :type: Optional[list]

      


.. py:class:: AveragePrecisionScore(**data: Any)


   Bases: :py:obj:`rhino_health.lib.metrics.base_metric.AggregatableMetric`

   
   Calculates the `Average Precision Score <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.average_precision_score.html#sklearn.metrics.average_precision_score>`_
















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   .. py:attribute:: y_true
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: y_score
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: average
      :type: Optional[str]
      :value: 'macro'

      

   .. py:attribute:: pos_label
      :type: Optional[Union[int, str]]
      :value: 1

      

   .. py:attribute:: sample_weight
      :type: Optional[list]

      


.. py:class:: BalancedAccuracyScore(**data: Any)


   Bases: :py:obj:`rhino_health.lib.metrics.base_metric.AggregatableMetric`

   
   Calculates the `Balanced Accuracy Score <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.balanced_accuracy_score.html#sklearn.metrics.balanced_accuracy_score>`_
















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   .. py:attribute:: y_true
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: y_pred
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: sample_weight
      :type: Optional[list]

      

   .. py:attribute:: adjusted
      :type: Optional[bool]
      :value: False

      


.. py:class:: BrierScoreLoss(**data: Any)


   Bases: :py:obj:`rhino_health.lib.metrics.base_metric.AggregatableMetric`

   
   Calculates the `Brier Score Loss <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.brier_score_loss.html#sklearn.metrics.brier_score_loss>`_
















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   .. py:attribute:: y_true
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: y_prob
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: sample_weight
      :type: Optional[list]

      

   .. py:attribute:: pos_label
      :type: Optional[Union[int, str]]

      


.. py:class:: CohenKappaScore(**data: Any)


   Bases: :py:obj:`rhino_health.lib.metrics.base_metric.AggregatableMetric`

   
   Calculates the `Cohen Kappa Score <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.cohen_kappa_score.html#sklearn.metrics.cohen_kappa_score>`_
















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   .. py:attribute:: y1
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: y2
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: labels
      :type: Optional[list]

      

   .. py:attribute:: weights
      :type: Optional[str]

      

   .. py:attribute:: sample_weight
      :type: Optional[list]

      


.. py:class:: ConfusionMatrix(**data: Any)


   Bases: :py:obj:`rhino_health.lib.metrics.base_metric.AggregatableMetric`

   
   Calculates the `Confusion Matrix <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html#sklearn.metrics.confusion_matrix>`_
















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   .. py:attribute:: y_true
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: y_pred
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: labels
      :type: Optional[list]

      

   .. py:attribute:: sample_weight
      :type: Optional[list]

      

   .. py:attribute:: normalize
      :type: Optional[bool]
      :value: True

      


.. py:class:: DCGScore(**data: Any)


   Bases: :py:obj:`rhino_health.lib.metrics.base_metric.AggregatableMetric`

   
   Calculates the `DCG Score <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.dcg_score.html#sklearn.metrics.dcg_score>`_
















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   .. py:attribute:: y_true
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: y_score
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: k
      :type: Optional[int]

      

   .. py:attribute:: log_base
      :type: Optional[int]
      :value: 2

      

   .. py:attribute:: sample_weight
      :type: Optional[list]

      

   .. py:attribute:: ignore_ties
      :type: Optional[bool]
      :value: False

      


.. py:class:: F1Score(**data: Any)


   Bases: :py:obj:`WeightedScore`

   
   Calculates the `F1 Score <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html#sklearn.metrics.f1_score>`_
















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   .. py:attribute:: y_pred
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

















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   .. py:attribute:: average
      :type: Optional[str]
      :value: 'binary'

      

















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   .. py:attribute:: labels
      :type: Optional[list]

      

















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   .. py:attribute:: pos_label
      :type: Optional[Union[int, str]]
      :value: 1

      

















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   .. py:attribute:: sample_weight
      :type: Optional[list]

      

















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.. py:class:: FBetaScore(**data: Any)


   Bases: :py:obj:`WeightedScore`

   
   Calculates the `F Beta Score <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.fbeta_score.html#sklearn.metrics.fbeta_score>`_
















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   .. py:attribute:: y_pred
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   .. py:attribute:: average
      :type: Optional[str]
      :value: 'binary'

      

















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   .. py:attribute:: labels
      :type: Optional[list]

      

















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   .. py:attribute:: pos_label
      :type: Optional[Union[int, str]]
      :value: 1

      

















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   .. py:attribute:: sample_weight
      :type: Optional[list]

      

















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.. py:class:: HammingLossMetric(**data: Any)


   Bases: :py:obj:`rhino_health.lib.metrics.base_metric.AggregatableMetric`

   
   Calculates the `Hamming Loss Metric <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.hamming_loss.html#sklearn.metrics.hamming_loss>`_
















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   .. py:attribute:: y_true
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: y_pred
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: sample_weight
      :type: Optional[list]

      


.. py:class:: HingeLossMetric(**data: Any)


   Bases: :py:obj:`rhino_health.lib.metrics.base_metric.AggregatableMetric`

   
   Calculates the `Hinge Loss Metric <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.hinge_loss.html#sklearn.metrics.hinge_loss>`_
















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   .. py:attribute:: y_true
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: pred_decision
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: labels
      :type: Optional[list]

      

   .. py:attribute:: sample_weight
      :type: Optional[list]

      


.. py:class:: JaccardScore(**data: Any)


   Bases: :py:obj:`rhino_health.lib.metrics.base_metric.AggregatableMetric`

   
   Calculates the `Jaccard Score <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.jaccard_score.html#sklearn.metrics.jaccard_score>`_
















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.. py:class:: LogLoss(**data: Any)


   Bases: :py:obj:`rhino_health.lib.metrics.base_metric.AggregatableMetric`

   
   Calculates the `Log Loss <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.jaccard_score.html#sklearn.metrics.log_loss>`_
















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   .. py:attribute:: y_true
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: y_pred
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: eps
      :type: Optional[float]

      

   .. py:attribute:: normalize
      :type: Optional[bool]
      :value: True

      

   .. py:attribute:: sample_weight
      :type: Optional[list]

      

   .. py:attribute:: labels
      :type: Optional[list]

      


.. py:class:: MatthewsCorrelationCoefficient(**data: Any)


   Bases: :py:obj:`rhino_health.lib.metrics.base_metric.AggregatableMetric`

   
   Calculates the `Matthews Correlation Coefficient <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.matthews_corrcoef.html#sklearn.metrics.matthews_corrcoef>`_
















   ..
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   .. py:attribute:: y_true
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: y_pred
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: sample_weight
      :type: Optional[list]

      


.. py:class:: NDCGScore(**data: Any)


   Bases: :py:obj:`rhino_health.lib.metrics.base_metric.AggregatableMetric`

   
   Calculates the `NDCG Score <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.ndcg_score.html#sklearn.metrics.ndcg_score>`_
















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   .. py:attribute:: y_true
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: y_score
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: k
      :type: Optional[int]

      

   .. py:attribute:: sample_weight
      :type: Optional[list]

      

   .. py:attribute:: ignore_ties
      :type: Optional[bool]
      :value: False

      


.. py:class:: PrecisionScore(**data: Any)


   Bases: :py:obj:`WeightedScore`

   
   Calculates the `Precision Score <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.precision_score.html#sklearn.metrics.precision_score>`_
















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      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

















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   .. py:attribute:: average
      :type: Optional[str]
      :value: 'binary'

      

















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   .. py:attribute:: labels
      :type: Optional[list]

      

















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   .. py:attribute:: pos_label
      :type: Optional[Union[int, str]]
      :value: 1

      

















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   .. py:attribute:: sample_weight
      :type: Optional[list]

      

















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.. py:class:: RecallScore(**data: Any)


   Bases: :py:obj:`WeightedScore`

   
   Calculates the `Recall Score <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.recall_score.html#sklearn.metrics.recall_score>`_
















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   .. py:attribute:: average
      :type: Optional[str]
      :value: 'binary'

      

















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   .. py:attribute:: labels
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      :value: 1

      

















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.. py:class:: TopKAccuracyScore(**data: Any)


   Bases: :py:obj:`rhino_health.lib.metrics.base_metric.AggregatableMetric`

   
   Calculates the `Top K Accuracy Score <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.top_k_accuracy_score.html#sklearn.metrics.top_k_accuracy_score>`_
















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   .. py:attribute:: y_true
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: y_score
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: k
      :type: Optional[int]
      :value: 2

      

   .. py:attribute:: normalize
      :type: Optional[bool]
      :value: True

      

   .. py:attribute:: sample_weight
      :type: Optional[list]

      

   .. py:attribute:: labels
      :type: Optional[list]

      


.. py:class:: ZeroOneLoss(**data: Any)


   Bases: :py:obj:`rhino_health.lib.metrics.base_metric.AggregatableMetric`

   
   Calculates the `Zero One Loss <https://scikit-learn.org/stable/modules/generated/sklearn.metrics.zero_one_loss.html#sklearn.metrics.zero_one_loss>`_
















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   .. py:attribute:: y_true
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: y_score
      :type: rhino_health.lib.metrics.filter_variable.FilterVariableTypeOrColumnName

      

   .. py:attribute:: normalize
      :type: Optional[bool]
      :value: True

      

   .. py:attribute:: sample_weight
      :type: Optional[list]