def classify_news():
s = session()
rows = s.query(News).filter(News.label == None).all()
model = NaiveBayesClassifier()
model.import_model('news_model.json')
predictions = model.predict([row.title for row in rows])
d = deque()
for new, pred in zip(rows, predictions):
if pred == 'good':
d.appendleft(new)
elif pred == 'never':
d.append(new)
return template('classify', rows=d)
