nannyml.performance_calculation.metrics.regression module

class nannyml.performance_calculation.metrics.regression.MAE(y_true: str, y_pred: str, threshold: nannyml.thresholds.Threshold, y_pred_proba: Optional[str] = None)

Bases: nannyml.performance_calculation.metrics.base.Metric

Mean Absolute Error metric.

Creates a new MAE instance.

class nannyml.performance_calculation.metrics.regression.MAPE(y_true: str, y_pred: str, threshold: nannyml.thresholds.Threshold, y_pred_proba: Optional[str] = None)

Bases: nannyml.performance_calculation.metrics.base.Metric

Mean Absolute Percentage Error metric.

Creates a new MAPE instance.

class nannyml.performance_calculation.metrics.regression.MSE(y_true: str, y_pred: str, threshold: nannyml.thresholds.Threshold, y_pred_proba: Optional[str] = None)

Bases: nannyml.performance_calculation.metrics.base.Metric

Mean Squared Error metric.

Creates a new MSE instance.

class nannyml.performance_calculation.metrics.regression.MSLE(y_true: str, y_pred: str, threshold: nannyml.thresholds.Threshold, y_pred_proba: Optional[str] = None)

Bases: nannyml.performance_calculation.metrics.base.Metric

Mean Squared Logarithmic Error metric.

Creates a new MSLE instance.

class nannyml.performance_calculation.metrics.regression.RMSE(y_true: str, y_pred: str, threshold: nannyml.thresholds.Threshold, y_pred_proba: Optional[str] = None)

Bases: nannyml.performance_calculation.metrics.base.Metric

Root Mean Squared Error metric.

Creates a new RMSE instance.

class nannyml.performance_calculation.metrics.regression.RMSLE(y_true: str, y_pred: str, threshold: nannyml.thresholds.Threshold, y_pred_proba: Optional[str] = None)

Bases: nannyml.performance_calculation.metrics.base.Metric

Root Mean Squared Logarithmic Error metric.

Creates a new RMSLE instance.