feat(prediction): correct dict

src/controllers/prediction_controller.py

@@ -78,9 +78,17 @@ def global_prediction_on_csv(file: UploadFile):
 
         # Chargement du modèle
         try:
-            model = joblib.load("src/models/L1_Logistic_v0.joblib")
+            saved = joblib.load("src/models/L1_Logistic_v0.joblib")
+            model = saved["model"]
+            scaler = saved["scaler"]
+            pca = saved.get("pca", None)
+            # features = saved["features"]
         except FileNotFoundError:
             raise HTTPException(status_code=500, detail="Modèle 'L1_Logistic_v0.joblib' introuvable")
+        # try:
+        #     model = joblib.load("src/models/L1_Logistic_v0.joblib")
+        # except FileNotFoundError:
+        #     raise HTTPException(status_code=500, detail="Modèle 'L1_Logistic_v0.joblib' introuvable")
 
         print("drop label column if exists")
 
@@ -92,6 +100,12 @@ def global_prediction_on_csv(file: UploadFile):
             
         print("features prepared, starting prediction")
 
+        # Standardisation
+        X = scaler.transform(X)
+
+        # PCA si utilisé
+        if pca is not None:
+            X = pca.transform(X)
         # Prédictions
         preds = model.predict(X)