dataeval.outputs¶

Output classes for DataEval to store function and method outputs as well as runtime metadata for reproducibility and logging.

Classes¶

`ExecutionMetadata`	Metadata about the execution of the function or method for the Output class.
`MetadataDistanceValues`	Statistics comparing metadata distance.
`NullModelMetrics`	Per-model results for null-model metrics
`SourceIndex`	The indices of the source image, box and channel.
`TrainValSplit`	Dataclass containing train and validation indices.

Output Classes¶

`BEROutput`	Output class for `ber()` estimator metric.
`BalanceOutput`	Output class for `balance()` bias metric.
`ClustererOutput`	Output class for `clusterer()`.
`CompletenessOutput`	Output from the completeness function.
`CoverageOutput`	Output class for `coverage()` bias metric.
`DimensionStatsOutput`	Output class for `dimensionstats()` stats metric.
`DivergenceOutput`	Output class for `divergence()` estimator metric.
`DiversityOutput`	Output class for `diversity()` bias metric.
`DriftMMDOutput`	Output class for `DriftMMD` (Maximum Mean Discrepancy) drift detector.
`DriftMVDCOutput`	Class wrapping the results of the classifier for drift detection and providing plotting functionality.
`DriftOutput`	Output class for univariate drift detectors.
`DuplicatesOutput`	Output class for `Duplicates` lint detector.
`HashStatsOutput`	Output class for `hashstats()` stats metric.
`ImageStatsOutput`	Output class for `imagestats()` stats metric.
`LabelParityOutput`	Output class for `label_parity()` bias metrics.
`LabelStatsOutput`	Output class for `labelstats()` stats metric.
`MetadataDistanceOutput`	Output class for results of ks_2samp featurewise comparisons of new metadata to reference metadata.
`MostDeviatedFactorsOutput`	Output class for results of `most_deviated_factors()` for OOD samples with metadata.
`NullModelMetricsOutput`	Output class for null-model metrics
`OODOutput`	Output class for predictions from out-of-distribution detectors.
`OODPredictorOutput`	Output class for results of `find_ood_predictors()` for the
`OODScoreOutput`	Output class for instance and feature scores from out-of-distribution detectors.
`OutliersOutput`	Output class for `Outliers` lint detector.
`ParityOutput`	Output class for `parity()` bias metrics.
`PixelStatsOutput`	Output class for `pixelstats()` stats metric.
`SplitDatasetOutput`	Output class containing test indices and a list of TrainValSplits.
`SufficiencyOutput`	Output class for `Sufficiency` workflow.
`UAPOutput`	Output class for `uap()` estimator metric.
`VisualStatsOutput`	Output class for `visualstats()` stats metric.