Upload 17 files

app.py

@@ -83,7 +83,12 @@ def Salary(model, workclass, education, marital_status, occupation, relationship
             scaler = pickle.load(f)
     elif model == 2:
         model_used = "Random Forest"
-        # Add Random Forest model
+        with open('models/best_rf_Salary_Classification.pkl', 'rb') as f:
+            loaded_model = pickle.load(f)
+
+        # Loading the scaler and transform the data
+        with open('models/z-score_scaler_rf_salary_classification.pkl', 'rb') as f:
+            scaler = pickle.load(f)
 
     new_data = {
         'age': age,
@@ -195,7 +200,12 @@ def Health(model, age, sex, bmi, children, smoker, region):
             scaler = pickle.load(f)
     elif model == 2:
         model_used = "Random Forest"
-        # Add Random Forest model
+        with open('models/best_rf_Charges_Classification.pkl', 'rb') as f:
+            loaded_model = pickle.load(f)
+
+        # Loading the scaler and transform the data
+        with open('models/z-score_scaler_rf_charges_classification.pkl', 'rb') as f:
+            scaler = pickle.load(f)
 
     #Inverting the dict to map the 'charges' values back to 'charges' labels
     inverse_mapping_charges = {

models/best_rf_Charges_Classification.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b6acb0e0ec78fbc3e05818778dffef502d6f9747b6c8e73378f45fc97f6885bf
+size 6975365

models/best_rf_Salary_Classification.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3b71f4d9c74e3746efdea7176c9506736902d76e5c23329dea06fc7b97a07746
+size 47028040

models/z-score_scaler_rf_charges_classification.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b268e1fa1b5a7b30164255adad3756ccd8222d9033db68e8237ac33ef2f5b3d5
+size 597

models/z-score_scaler_rf_salary_classification.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b268a96764622c1bac3951b1c898d6b04a8294db590af190cfff6f7440a8bc9c
+size 726