evidently.metrics.classification_performance

Submodules

base_classification_metric module

class ThresholdClassificationMetric(probas_threshold: Optional[float], k: Optional[Union[float, int]])

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class_balance_metric module

class ClassificationClassBalance()

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class ClassificationClassBalanceRenderer(color_options: Optional[ColorOptions] = None)

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class ClassificationClassBalanceResult(plot_data: Dict[str, int])

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class_separation_metric module

class ClassificationClassSeparationPlot()

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class ClassificationClassSeparationPlotRenderer(color_options: Optional[ColorOptions] = None)

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class ClassificationClassSeparationPlotResults(target_name: str, current_plot: Optional[pandas.core.frame.DataFrame] = None, reference_plot: Optional[pandas.core.frame.DataFrame] = None)

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classification_dummy_metric module

class ClassificationDummyMetric(probas_threshold: Optional[float] = None, k: Optional[Union[float, int]] = None)

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class ClassificationDummyMetricRenderer(color_options: Optional[ColorOptions] = None)

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class ClassificationDummyMetricResults(dummy: DatasetClassificationQuality, by_reference_dummy: Optional[DatasetClassificationQuality], model_quality: Optional[DatasetClassificationQuality], metrics_matrix: dict)

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classification_quality_metric module

class ClassificationQualityMetric(probas_threshold: Optional[float] = None, k: Optional[Union[float, int]] = None)

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class ClassificationQualityMetricRenderer(color_options: Optional[ColorOptions] = None)

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class ClassificationQualityMetricResult(current: DatasetClassificationQuality, reference: Optional[DatasetClassificationQuality], target_name: str)

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confusion_matrix_metric module

class ClassificationConfusionMatrix(probas_threshold: Optional[float] = None, k: Optional[Union[float, int]] = None)

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class ClassificationConfusionMatrixRenderer(color_options: Optional[ColorOptions] = None)

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class ClassificationConfusionMatrixResult(current_matrix: ConfusionMatrix, reference_matrix: Optional[ConfusionMatrix])

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pr_curve_metric module

class ClassificationPRCurve()

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class ClassificationPRCurveRenderer(color_options: Optional[ColorOptions] = None)

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class ClassificationPRCurveResults(current_pr_curve: Optional[dict] = None, reference_pr_curve: Optional[dict] = None)

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pr_table_metric module

class ClassificationPRTable()

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class ClassificationPRTableRenderer(color_options: Optional[ColorOptions] = None)

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class ClassificationPRTableResults(current_pr_table: Optional[dict] = None, reference_pr_table: Optional[dict] = None)

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probability_distribution_metric module

class ClassificationProbDistribution()

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class ClassificationProbDistributionRenderer(color_options: Optional[ColorOptions] = None)

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class ClassificationProbDistributionResults(current_distribution: Optional[Dict[str, list]], reference_distribution: Optional[Dict[str, list]])

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quality_by_class_metric module

class ClassificationQualityByClass(probas_threshold: Optional[float] = None, k: Optional[Union[float, int]] = None)

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class ClassificationQualityByClassRenderer(color_options: Optional[ColorOptions] = None)

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class ClassificationQualityByClassResult(columns: DatasetColumns, current_metrics: dict, current_roc_aucs: Optional[list], reference_metrics: Optional[dict], reference_roc_aucs: Optional[dict])

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quality_by_feature_table module

class ClassificationQualityByFeatureTable(columns: Optional[List[str]] = None)

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class ClassificationQualityByFeatureTableRenderer(color_options: Optional[ColorOptions] = None)

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class ClassificationQualityByFeatureTableResults(current_plot_data: pandas.core.frame.DataFrame, reference_plot_data: Optional[pandas.core.frame.DataFrame], target_name: str, curr_predictions: PredictionData, ref_predictions: Optional[PredictionData], columns: List[str])

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roc_curve_metric module

class ClassificationRocCurve()

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class ClassificationRocCurveRenderer(color_options: Optional[ColorOptions] = None)

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class ClassificationRocCurveResults(current_roc_curve: Optional[dict] = None, reference_roc_curve: Optional[dict] = None)

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