Update app.py

app.py

@@ -8,7 +8,7 @@ from sklearn.tree import DecisionTreeRegressor
 from sklearn.ensemble import RandomForestRegressor, StackingRegressor
 from sklearn.preprocessing import FunctionTransformer, MinMaxScaler, StandardScaler, LabelEncoder
 from sklearn.model_selection import train_test_split
-# import xgboost
+import xgboost
 
 import tqdm
 from tqdm.auto import trange, tqdm
@@ -81,7 +81,7 @@ def run_():
     X_train = pd.DataFrame(X_train, columns = X.columns)
     X_test = pd.DataFrame(X_test, columns = X.columns)
     dd = pd.concat([X_train, X_test], axis = 0)
-    xgbr = sklearn.ensemble.RandomForestRegressor(random_state = 42)
+    xgbr = xgboost.XGBRegressor(random_state = 42)
     xgbr.fit(dd.drop(["Flag"], axis = 1), y_train)
     print(X_train.drop(["Flag"], axis = 1).columns)
     def make_predictions(domain_, year_, flag_, item_, unit_, flag_description_, element_, mean_temp_, total_temp_, mrh_, trh_, mrf_, trf_, mean_fert_, total_fert_, mean_pest_, total_pest_):