Ensure appropriate behavior for `GridSearchCV`, etc.

[gsganden]

This code plots the model as if it were a classification model rather than a regression model:

import sklearn.datasets
from model_inspector import get_inspector
from sklearn.linear_model import LinearRegression
from sklearn.model_selection import GridSearchCV

X_diabetes, y_diabetes = sklearn.datasets.load_diabetes(return_X_y=True, as_frame=True)
X_diabetes = X_diabetes.iloc[:, [0]]

grid = GridSearchCV(LinearRegression(), {}).fit(X_diabetes, y_diabetes)

inspector = get_inspector(grid, X_diabetes, y_diabetes)

ax = inspector.plot()

It would ideally recognize that grid.best_estimator_ is a regression model and plot it accordingly:

inspector = get_inspector(grid.best_estimator_, X_diabetes, y_diabetes)

ax = inspector.plot()

Alternatively, it could refuse to plot, requiring the user to make the inspector from grid.best_estimator_.