FeatureDriftSummary

Summary of important model monitoring statistics for features available in a model monitoring instance

KEY TYPE Description
featureIndex List[dict] A list of dicts of eligible feature names and corresponding overall feature drift measures.
name str Name of feature.
distance float Symmetric sum of KL divergences between the training distribution and the range of values in the specified window.
jsDistance float JS divergence between the training distribution and the range of values in the specified window.
wsDistance float Wasserstein distance between the training distribution and the range of values in the specified window.
ksStatistic float Kolmogorov-Smirnov statistic computed between the training distribution and the range of values in the specified window.
predictionDrift float Drift for the target column.
targetColumn str Target column name.
dataIntegrityTimeseries dict Frequency vs Data Integrity Violation Charts.
nestedSummary List[dict] Summary of model monitoring statistics for nested features.
psi float Population stability index computed between the training distribution and the range of values in the specified window.
csi float Characteristic Stability Index computed between the training distribution and the range of values in the specified window.
chiSquare float Chi-square statistic computed between the training distribution and the range of values in the specified window.
nullViolations NullViolation A list of dicts of feature names and a description of corresponding null violations.
rangeViolations RangeViolation A list of dicts of numerical feature names and corresponding prediction range discrepancies.
catViolations CategoricalRangeViolation A list of dicts of categorical feature names and corresponding prediction range discrepancies.