def svm_predict_3_points(rows):
data = preprocessing.generate_BOW(rows, svm_3_dict)
y_predict = svm_3_clf.predict(data)
return [each + 1 for each in list(y_predict)]
def naive_bayes_predict_3_points(rows):
data = preprocessing.generate_BOW(rows, naive_3_dict)
y_predict = naive_3_clf.predict(data)
return [each + 1 for each in list(y_predict)]
def svm_predict_2_points(rows):
data = preprocessing.generate_BOW(rows, svm_2_dict)
y_predict = svm_2_clf.predict(data)
return [each + 1 if each == -1 else each for each in list(y_predict)]
def predict(self, txt):
txt = preprocessing.generate_BOW(txt, self.dic, n_gram=self.n_gram, use_bern=self.use_bern)
y_pred = self.clf.predict(txt)
return y_pred