परफॉर्मेंस का मूल्यांकन

# Use the best hyperparameters from before to fit a random forest model
rfr = RandomForestRegressor(n_estimators=200, max_depth=3, max_features=____, random_state=42)
rfr.fit(train_features, train_targets)

# Make predictions with our model
train_predictions = rfr.predict(____)
test_predictions = ____

# Create a scatter plot with train and test actual vs predictions
plt.scatter(train_targets, train_predictions, label='train')
plt.scatter(____)
plt.legend()
plt.show()