Update app.py

app.py

@@ -7,12 +7,13 @@ with open('./rf_cv_waze.pickle' , 'rb') as file:
 
 # Define the function for making predictions
 def salifort(sessions, drives, total_sessions, n_days_after_onboarding, total_navigations_fav1, total_navigations_fav2, driven_km_drives, duration_minutes_drives, activity_days, driving_days, km_per_driving_day, percent_sessions_in_last_month, professional_driver, total_sessions_per_day, km_per_hour, km_per_drive, percent_of_drives_to_favorite, device2):
-    inputs = [['sessions', 'drives', 'total_sessions', 'n_days_after_onboarding',
-       'total_navigations_fav1', 'total_navigations_fav2', 'driven_km_drives',
-       'duration_minutes_drives', 'activity_days', 'driving_days',
-       'km_per_driving_day', 'percent_sessions_in_last_month',
-       'professional_driver', 'total_sessions_per_day', 'km_per_hour',
-       'km_per_drive', 'percent_of_drives_to_favorite', 'device2']]
+    inputs = [[ float('sessions'), float('drives'), float('total_sessions'), float('n_days_after_onboarding'),
+                float('total_navigations_fav1'), float('total_navigations_fav2'), float('driven_km_drives'),
+                float('duration_minutes_drives'), float('activity_days'), float('driving_days'),
+                float('km_per_driving_day'), float('percent_sessions_in_last_month'),
+                float('professional_driver'), float('total_sessions_per_day'), float('km_per_hour'),
+                float('km_per_drive'), float('percent_of_drives_to_favorite'), float('device2')
+                ]]
     prediction = model.predict(inputs)
     prediction_value = prediction[0]
     if prediction_value == 0: