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)

Bases: 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)

Bases: 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)

Bases: 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)

Bases: 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)

Bases: 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)

Bases: Metric

Specificity metric.

Creates a new Specificity instance.