abacusai.embedding_feature_drift_distribution

Module Contents

Classes

EmbeddingFeatureDriftDistribution

Feature distribution for embeddings

class abacusai.embedding_feature_drift_distribution.EmbeddingFeatureDriftDistribution(client, distance=None, jsDistance=None, wsDistance=None, ksStatistic=None, averageDrift={})

Bases: abacusai.return_class.AbstractApiClass

Feature distribution for embeddings

Parameters:
  • client (ApiClient) – An authenticated API Client instance

  • distance (list) – Histogram data of KL divergences between the training distribution and the range of values in the specified window.

  • jsDistance (list) – Histogram data of JS divergence between the training distribution and the range of values in the specified window.

  • wsDistance (list) – Histogram data of Wasserstein distance between the training distribution and the range of values in the specified window.

  • ksStatistic (list) – Histogram data of Kolmogorov-Smirnov statistic computed between the training distribution and the range of values in the specified window.

  • averageDrift (DriftTypesValue) – Average drift embedding for each type of drift

__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