Upload app.py

app.py

@@ -57,7 +57,7 @@ for train_index, test_index in cv.split(x1, y1):
     x1_train_fold, y1_train_fold = resampler.fit_resample(x1_train_fold, y1_train_fold)
     y1_model = TabPFNClassifier(device='cuda', N_ensemble_configurations=8)
     y1_model.fit(x1_train_fold, y1_train_fold, overwrite_warning=True)
-    y1_calib_model = CalibratedClassifierCV(tabpfn, method='isotonic', cv='prefit')
+    y1_calib_model = CalibratedClassifierCV(y1_model, method='isotonic', cv='prefit')
     y1_calib_model.fit(x1_valid_fold, y1_valid_fold)
 
 for train_index, test_index in cv.split(x2, y2):
@@ -66,7 +66,7 @@ for train_index, test_index in cv.split(x2, y2):
     x2_train_fold, y2_train_fold = resampler.fit_resample(x2_train_fold, y2_train_fold)
     y2_model = TabPFNClassifier(device='cuda', N_ensemble_configurations=8)
     y2_model.fit(x2_train_fold, y2_train_fold, overwrite_warning=True)
-    y2_calib_model = CalibratedClassifierCV(tabpfn, method='isotonic', cv='prefit')
+    y2_calib_model = CalibratedClassifierCV(y2_model, method='isotonic', cv='prefit')
     y2_calib_model.fit(x2_valid_fold, y2_valid_fold)
 
 for train_index, test_index in cv.split(x3, y3):
@@ -75,7 +75,7 @@ for train_index, test_index in cv.split(x3, y3):
     x3_train_fold, y3_train_fold = resampler.fit_resample(x3_train_fold, y3_train_fold)
     y3_model = TabPFNClassifier(device='cuda', N_ensemble_configurations=8)
     y3_model.fit(x3_train_fold, y3_train_fold, overwrite_warning=True)
-    y3_calib_model = CalibratedClassifierCV(tabpfn, method='isotonic', cv='prefit')
+    y3_calib_model = CalibratedClassifierCV(y3_model, method='isotonic', cv='prefit')
     y3_calib_model.fit(x3_valid_fold, y3_valid_fold)