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. |