from sklearn.linear_model import Ridge
from sklearn.model_selection import train_test_split

from yellowbrick.datasets import load_concrete
from yellowbrick.regressor import ResidualsPlot

# Load a regression dataset
X, y = load_concrete()

# Create the train and test data
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

# Instantiate the linear model and visualizer
model = Ridge()
visualizer = ResidualsPlot(model)

visualizer.fit(X_train, y_train)  # Fit the training data to the visualizer
visualizer.score(X_test, y_test)  # Evaluate the model on the test data
visualizer.show()                 # Finalize and render the figure