Update app.py

app.py

@@ -7,6 +7,10 @@ from sklearn.model_selection import train_test_split
 from sklearn.datasets import fetch_california_housing
 import pickle
 
+from sklearn import datasets
+
+from sklearn.metrics import mean_squared_error, r2_score
+
 # Load the data
 california = fetch_california_housing()
 df = pd.DataFrame(california.data, columns=california.feature_names)
@@ -52,7 +56,9 @@ model.fit(X_train, y_train)
 y_pred = model.predict(X_test)
 
 # Evaluating the model
-
+mse = mean_squared_error(y_test, y_pred)
+rmse = np.sqrt(mse)
+r2 = r2_score(y_test, y_pred)