Update app.py

app.py

@@ -89,7 +89,7 @@ if ensemble_type == "bagging":
     test_loss = []
     train_loss = []
     for i in range(1, estimator_number):
-        model = BaggingRegressor(estimator=estimator, n_estimators=i, random_state=45)
+        model = BaggingRegressor(base_estimator=estimator, n_estimators=i, random_state=45)
         model.fit(X_train, y_train)
         y_pred = model.predict(X_test)
         temp = mean_squared_error(y_test, y_pred)
@@ -112,7 +112,7 @@ elif ensemble_type == "boosting":
     test_loss = []
     estimator = estimator_model(model_type)
     for i in range(1, estimator_number):
-        model = AdaBoostRegressor(n_estimators=i, estimator=estimator)
+        model = AdaBoostRegressor(n_estimators=i, base_estimator=estimator)
         model.fit(X_train, y_train)
         y_pred = model.predict(X_test)
         test_loss.append(mean_squared_error(y_test, y_pred))