Regression Module

Classes:

Name	Description
BaseRegressionDecision	Base class for regression-based decision-making.
AdvancedRegressionDecision	Advanced class for regression-based decision-making.

BaseRegressionDecision

BaseRegressionDecision(estimator, *, threshold=0.0)

Bases: BaseDecision, ABC

Base class for regression-based decision-making.

This class provides a common interface for regression-based decision-making algorithms.

It calls estimator.predict(X) to predict the output values.

When using this class?

• When the decision is based on the output of a regression model.

Parameters:

Name	Type	Description	Default
estimator	BaseEstimator	The estimator used to predict the output values.	required
threshold	float	The threshold for the prediction. If the prediction is less than or equal to the threshold, the decision is NaN; otherwise, the prediction.	0.0

Attributes:

Name	Type	Description
estimator	BaseEstimator	The estimator used to predict the output values.
threshold	float	The threshold for the residual.

Methods:

Name	Description
get_params	Get the parameters of the estimator.
make_prediction	Predict the output values based on the input data.

Source code in risk_control/decision/regression.py

def __init__(
    self,
    estimator: BaseEstimator,
    *,
    threshold: float = 0.0,
) -> None:
    super().__init__(estimator)
    self.threshold = threshold

threshold instance-attribute

threshold = threshold

get_params

get_params()

Get the parameters of the estimator.

Returns:

Name	Type	Description
params	dict	The parameters of the estimator.

Source code in risk_control/decision/regression.py

def get_params(self) -> Dict[str, Any]:
    """
    Get the parameters of the estimator.

    Returns
    -------
    params : dict
        The parameters of the estimator.
    """
    return {"threshold": self.threshold}

make_prediction

make_prediction(X)

Predict the output values based on the input data.

Parameters:

Name	Type	Description	Default
X	ndarray	The input data for making predictions.	required

Returns:

Type	Description
ndarray	The predicted output values based on the input data.

Source code in risk_control/decision/regression.py

def make_prediction(self, X: np.ndarray) -> np.ndarray:
    """
    Predict the output values based on the input data.

    Parameters
    ----------
    X : np.ndarray
        The input data for making predictions.

    Returns
    -------
    np.ndarray
        The predicted output values based on the input data.
    """
    return self.estimator.predict(X)

AdvancedRegressionDecision

AdvancedRegressionDecision(
    estimator, residual, *, threshold=1.0
)

Bases: BaseDecision, ABC

Advanced class for regression-based decision-making.

This class provides a common interface for regression-based decision-making algorithms based on residuals.

It calls estimator.predict(X) to predict the output values and residual.predict(X) to predict the residuals.

When using this class?

• When the prediction and residual are estimated separately.
• When the decision is based on the residual.

Parameters:

Name	Type	Description	Default
estimator	BaseEstimator	The estimator used to predict the output values.	required
residual	BaseEstimator	The estimator used to predict the residuals.	required
threshold	float	The threshold for the residual. If the residual is less than or equal to the threshold, the prediction is returned; otherwise, NaN. The default is 0.0.	1.0

Attributes:

Name	Type	Description
estimator	BaseEstimator	The estimator used to predict the output values.
residual	BaseEstimator	The estimator used to predict the residuals.
threshold	float	The threshold for the residual.

Methods:

Name	Description
get_params	Get the parameters of the estimator.
make_prediction	Predict the output values and residuals for the input data.

Source code in risk_control/decision/regression.py

def __init__(
    self,
    estimator: BaseEstimator,
    residual: BaseEstimator,
    *,
    threshold: float = 1.0,
) -> None:
    super().__init__(estimator)
    self.residual = residual
    self.threshold = threshold

residual instance-attribute

residual = residual

threshold instance-attribute

threshold = threshold

get_params

get_params()

Get the parameters of the estimator.

Returns:

Name	Type	Description
params	dict	The parameters of the estimator.

Source code in risk_control/decision/regression.py

def get_params(self) -> Dict[str, Any]:
    """
    Get the parameters of the estimator.

    Returns
    -------
    params : dict
        The parameters of the estimator.
    """
    return {"threshold": self.threshold}

make_prediction

make_prediction(X)

Predict the output values and residuals for the input data.

Parameters:

Name	Type	Description	Default
X	ndarray	The input data for which to predict the output values and residuals.	required

Returns:

Type	Description
Tuple[ndarray, ndarray]	The predicted output values and residuals. The first element is the predicted output values, and the second element is the predicted residuals.

Source code in risk_control/decision/regression.py

def make_prediction(self, X: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
    """
    Predict the output values and residuals for the input data.

    Parameters
    ----------
    X : np.ndarray
        The input data for which to predict the output values and residuals.

    Returns
    -------
    Tuple[np.ndarray, np.ndarray]
        The predicted output values and residuals.
        The first element is the predicted output values, and the second element
        is the predicted residuals.
    """
    return self.estimator.predict(X), self.residual.predict(X)