Update app.py

app.py

@@ -5,7 +5,7 @@ import matplotlib.pyplot as plt
 from sklearn.tree import plot_tree, export_text
 import seaborn as sns
 from sklearn.preprocessing import LabelEncoder
-import pickle
+import joblib
 
 def load_model_and_data():
     # Ici vous chargeriez votre modèle et données
@@ -14,8 +14,7 @@ def load_model_and_data():
     # X = loaded_X
     # y = loaded_y
     # feature_names = X.columns
-    with open('DecisionTreeModel.pkl', 'rb') as f:
-        model = pickle.load(f)
+    model = joblib.load('DecisionTreeModel.joblib')
     data = pd.read_csv('exported_named_train.csv')
     X = data.drop("Target", axis=1)
     y = data['Target']