Update app.py

app.py

@@ -10,7 +10,8 @@ data = pd.read_csv("mldata.csv")
 
 
 #load prediction model from notebook
-pickleFile = open('rfweights (1).pkl','rb')
+# pickleFile = open('rfweights (1).pkl','rb')
+pickelFile=open('dtreeweights.pkl','rb')
 rfmodel = pickle.load(pickleFile)
 
 #Obtain the categorical/nominal data because it is not coded according (but based on the first occurence, first come first assign number)