abacusai.drift_distribution

Classes

FeatureDistribution

For a single feature, how it has changed in the training data versus some specified window

AbstractApiClass

DriftDistribution

How actuals or predicted values have changed in the training data versus predicted data

Module Contents

class abacusai.drift_distribution.FeatureDistribution(client, type=None, trainingDistribution=None, predictionDistribution=None, numericalTrainingDistribution=None, numericalPredictionDistribution=None, trainingStatistics=None, predictionStatistics=None)

Bases: abacusai.return_class.AbstractApiClass

For a single feature, how it has changed in the training data versus some specified window

Parameters:

  • client (ApiClient) – An authenticated API Client instance

  • type (str) – Data type of values in each distribution, typically ‘categorical’ or ‘numerical’.

  • trainingDistribution (dict) – A dict describing the range of values in the training distribution.

  • predictionDistribution (dict) – A dict describing the range of values in the specified window.

  • numericalTrainingDistribution (dict) – A dict describing the summary statistics of the numerical training distribution.

  • numericalPredictionDistribution (dict) – A dict describing the summary statistics of the numerical prediction distribution.

  • trainingStatistics (dict) – A dict describing summary statistics of values in the training distribution.

  • predictionStatistics (dict) – A dict describing summary statistics of values in the specified window.

__repr__()

Return repr(self).

to_dict()

Get a dict representation of the parameters in this class

Returns:

The dict value representation of the class parameters

Return type:

dict

class abacusai.drift_distribution.AbstractApiClass(client, id)
__eq__(other)

Return self==value.

_get_attribute_as_dict(attribute)
class abacusai.drift_distribution.DriftDistribution(client, trainColumn=None, predictedColumn=None, metrics=None, distribution={})

Bases: abacusai.return_class.AbstractApiClass

How actuals or predicted values have changed in the training data versus predicted data

Parameters:

  • client (ApiClient) – An authenticated API Client instance

  • trainColumn (str) – The feature name in the train table.

  • predictedColumn (str) – The feature name in the prediction table.

  • metrics (dict) – Drift measures.

  • distribution (FeatureDistribution) – A FeatureDistribution, how the training data compares to the predicted data.

__repr__()

Return repr(self).

to_dict()

Get a dict representation of the parameters in this class

Returns:

The dict value representation of the class parameters

Return type:

dict