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. |