inspection.predictions.plot_actual_vs_predicted

inspection.predictions.plot_actual_vs_predicted(
    y_test,
    y_pred,
    title=None,
    show=True,
    filename=None,
)

Plot actual vs. predicted values.

Parameters

Name	Type	Description	Default
y_test	np.ndarray	True values.	required
y_pred	np.ndarray	Predicted values.	required
title	str	Title of the plot. Defaults to None.	None
show	bool	If True, the plot is shown. Defaults to True.	True
filename	str	Name of the file to save the plot. Defaults to None.	None

Returns

Name	Type	Description
	NoneType	None

Examples

>>> from sklearn.datasets import load_diabetes
    from sklearn.linear_model import LinearRegression
    from spotoptim.inspection import plot_actual_vs_predicted
    X, y = load_diabetes(return_X_y=True)
    lr = LinearRegression()
    lr.fit(X, y)
    y_pred = lr.predict(X)
    plot_actual_vs_predicted(y, y_pred)