Update app.py

app.py

@@ -110,7 +110,7 @@ y1_model = y1_model.fit(x1, y1, overwrite_warning=True)
 y1_calib_model = CalibratedClassifierCV(y1_model, method='isotonic', cv='prefit')
 y1_calib_model = y1_calib_model.fit(x1_valid, y1_valid)
 
-y1_explainer = shap.Explainer(y1_model.predict, x1)
+y1_explainer = shap.Explainer(y1_calib_model.predict, x1)
 
 
 from tabpfn import TabPFNClassifier
@@ -122,7 +122,7 @@ y2_model = y2_model.fit(x2, y2, overwrite_warning=True)
 y2_calib_model = CalibratedClassifierCV(y2_model, method='isotonic', cv='prefit')
 y2_calib_model = y2_calib_model.fit(x2_valid, y2_valid)
 
-y2_explainer = shap.Explainer(y2_model.predict, x2)
+y2_explainer = shap.Explainer(y2_calib_model.predict, x2)
 
 
 from tabpfn import TabPFNClassifier
@@ -134,7 +134,7 @@ y3_model = y3_model.fit(x3, y3, overwrite_warning=True)
 y3_calib_model = CalibratedClassifierCV(y3_model, method='isotonic', cv='prefit')
 y3_calib_model = y3_calib_model.fit(x3_valid, y3_valid)
 
-y3_explainer = shap.Explainer(y3_model.predict, x3)
+y3_explainer = shap.Explainer(y3_calib_model.predict, x3)
 
 
 from tabpfn import TabPFNClassifier
@@ -146,7 +146,7 @@ y4_model = y4_model.fit(x4, y4, overwrite_warning=True)
 y4_calib_model = CalibratedClassifierCV(y4_model, method='isotonic', cv='prefit')
 y4_calib_model = y4_calib_model.fit(x4_valid, y4_valid)
 
-y4_explainer = shap.Explainer(y4_model.predict, x4)
+y4_explainer = shap.Explainer(y4_calib_model.predict, x4)
 
 
 output_y1 = (