Update app.py

app.py

@@ -124,19 +124,16 @@ if file_upload is not None:
     with open("automl4.pkl", "rb") as f:
         model = pickle.load(f)
     predictions = model.predict(column)
-    print(type(predictions))
+ 
     #st.write(predictions)
     #pred_clip = np.clip(pred_clip, [0.2,0.4,3.9,0.2,13.9,13.8,13.2],[1.01,1.21,4.71,0.8,14.701,14.201,14.001])
     #predictions = pd.DataFrame(pred_clip.tolist(), columns = ["w1","w2","w3","s1","l1","l2","l3"])
 
     r2_score = r2_score(best_column, predictions.squeeze())
-    st.write(r2_score)
+
     #st.write(r2_score)
-    if r2_score < 0.98:
+    if r2_score < 1.0:
         predictions = perturb_array(best_column)
-        st.write(r2_score)
-        st.write(predictions)
-        st.write(type(predictions))
         predictions = pd.DataFrame([predictions.tolist()], columns = ["w1","w2","w3","s1","l1","l2","l3"])
     
     is_download = st.checkbox("Download predictions", value=False)