nannyml.drift package
Subpackages
Submodules
Module contents
NannyML drift detection module.
This module contains ways to detect both univariate (within a single continuous or categorical column) and multivariate (across multiple columns) drift.
The univariate drift detection methods include:
Kolmogorov-Smirnov statistic (continuous)
Wasserstein distance (continuous)
Chi-squared statistic (categorical)
L-infinity distance (categorical)
Jensen-Shannon distance
Hellinger distance
The multivariate drift detection methods include:
Data reconstruction error: detects drift by performing dimensionality reduction on the model inputs and then applying the inverse transformation on the latent (reduced) space.