abacusai.drift_distributions
Classes
How actuals or predicted values have changed in the training data versus predicted data |
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For either actuals or predicted values, how it has changed in the training data versus some specified window |
Module Contents
- class abacusai.drift_distributions.DriftDistribution(client, trainColumn=None, predictedColumn=None, metrics=None, distribution={})
Bases:
abacusai.return_class.AbstractApiClassHow 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).
- class abacusai.drift_distributions.AbstractApiClass(client, id)
- __eq__(other)
Return self==value.
- _get_attribute_as_dict(attribute)
- class abacusai.drift_distributions.DriftDistributions(client, labelDrift={}, predictionDrift={}, bpPredictionDrift={})
Bases:
abacusai.return_class.AbstractApiClassFor either actuals or predicted values, how it has changed in the training data versus some specified window
- Parameters:
client (ApiClient) – An authenticated API Client instance
labelDrift (DriftDistribution) – A DriftDistribution describing column names and the range of values for label drift.
predictionDrift (DriftDistribution) – A DriftDistribution describing column names and the range of values for prediction drift.
bpPredictionDrift (DriftDistribution) – A DriftDistribution describing column names and the range of values for prediction drift, when the predictions come from BP.
- __repr__()
Return repr(self).