Update app.py

app.py

@@ -8,16 +8,16 @@ def pecho(radio,suavidad,puntos_concavidad,area,compacidad,concavidad):
     model = load('tomatelo_a_pecho_regr.joblib')
     df = pd.DataFrame.from_dict(
         {
-            "Radio" : [radio],
-            "Suavidad" : [suavidad],
-            "Puntos_concavidad" : [puntos_concavidad],
-            "Area" : [area],
-            "Compacidad" : [compacidad],
-            "Concavidad" : [concavidad],
+            "radio_medio" : [radio],
+            "suavidad_media" : [suavidad],
+            "puntos_concavidad_media" : [puntos_concavidad],
+            "area_ee" : [area],
+            "compacidad_ee" : [compacidad],
+            "concavidad_extremo" : [concavidad],
                                  
         }
     )
-       
+         
     pred = model.predict(df)[0]
     if pred=='M':
       predicted="Las medidas indican que se trata de un caso maligno"
@@ -38,9 +38,9 @@ iface = gr.Interface(
 
     "text",
     examples=[
-        [40,True,120,80,"High","Normal",0,0,1,168,62,21],
-        [35,False,150,60,"Very High","Normal",0,0,1,143,52,31],
-        [60,True,160,70,"High","High",1,1,0,185,90,23],
+        [13.4,0.11,0.08,33.67,0.23,0.51],
+        [13.21,0.087,0.02,17.58,0.008,0.13],
+        [14.26,0.065,0.013,20.56,0.013,0.15],
     ],
     interpretation="default",
     title = 'Modelo de clasificación para tumores benignos y malignos de mama',