Update app.py

app.py

@@ -15,7 +15,7 @@ nltk.download('stopwords')
 
 ps = PorterStemmer()
 
-def preprocess_for_bow(text):
+def preprocess_for_bow_and_tfidf(text):
     corpus = []
     text = re.sub('[^a-zA-Z0-9$£€¥%]',' ',text)
     text = text.lower()
@@ -37,6 +37,7 @@ def classify(text,choice):
       features = vectorizer.transform(corpus).toarray()
       prediction = nb_classifier.predict(features)
   elif(choice == 2):
+      corpus = preprocess_for_bow_and_tfidf
       features = tfidf_vectorizer.transform(corpus).toarray()
       prediction = random_forest.predict(features)
   if(prediction == 1):