nannyml.performance_calculation.metrics.multiclass_classification module¶
Module containing metric utilities and implementations.
- class nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationAUROC(y_true: str, y_pred: str, y_pred_proba: Optional[Union[str, Dict[str, str]]] = None)[source]¶
Bases:
nannyml.performance_calculation.metrics.base.Metric
Area under Receiver Operating Curve metric.
Creates a new AUROC instance.
- class nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationAccuracy(y_true: str, y_pred: str, y_pred_proba: Optional[Union[str, Dict[str, str]]] = None)[source]¶
Bases:
nannyml.performance_calculation.metrics.base.Metric
Accuracy metric.
Creates a new Accuracy instance.
- class nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationF1(y_true: str, y_pred: str, y_pred_proba: Optional[Union[str, Dict[str, str]]] = None)[source]¶
Bases:
nannyml.performance_calculation.metrics.base.Metric
F1 score metric.
Creates a new F1 instance.
- class nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationPrecision(y_true: str, y_pred: str, y_pred_proba: Optional[Union[str, Dict[str, str]]] = None)[source]¶
Bases:
nannyml.performance_calculation.metrics.base.Metric
Precision metric.
Creates a new Precision instance.
- class nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationRecall(y_true: str, y_pred: str, y_pred_proba: Optional[Union[str, Dict[str, str]]] = None)[source]¶
Bases:
nannyml.performance_calculation.metrics.base.Metric
Recall metric, also known as ‘sensitivity’.
Creates a new Recall instance.
- class nannyml.performance_calculation.metrics.multiclass_classification.MulticlassClassificationSpecificity(y_true: str, y_pred: str, y_pred_proba: Optional[Union[str, Dict[str, str]]] = None)[source]¶
Bases:
nannyml.performance_calculation.metrics.base.Metric
Specificity metric.
Creates a new Specificity instance.