Update app.py

app.py

@@ -13,34 +13,6 @@ from imblearn.over_sampling import SMOTE
 import gradio as gr
 import datasets
 
-sft = ['age', 'serum_creatinine','ejection_fraction']
-
-#data_features = datasets.Features({'text': Value('string'), 'label': ClassLabel(names=sft)})
-
-
-
-#`my_dataset_dictionary['train'][['age', 'serum_creatinine', 'ejection_fraction']]`. Available splits: ['train']"
-
-data = datasets.load_dataset("Boadiwaa/heart_data", {"train": [sft]}, ignore_verifications = True)
-
-Features = sft
-
-x = data[Features]
-y = data["DEATH_EVENT"]
-
-x_train,x_test,y_train,y_test = train_test_split(x,y, test_size=0.2,shuffle=False)
-
-smote = SMOTE(sampling_strategy = 'minority', random_state = 2)
-x_SMOTE, y_SMOTE = smote.fit_resample(x_train,y_train)
-
-svc = SVC()
-
-svc.fit(x_SMOTE, y_SMOTE)
-
-with open("model.pkl", "wb") as f:
-    pickle.dump(svc, f)
-    
-
 def make_prediction(age,serum_creatinine,ejection_fraction):
     with open("model.pkl", "rb") as f:
         svc  = pickle.load(f)