inspection.predictions
inspection.predictions
Functions
| Name | Description |
|---|---|
| plot_actual_vs_predicted | Plot actual vs. predicted values. |
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)