Sentiment-based text categorization(for short,sentiment classification) is a task of classifying text according to the subjective information in the text.Nowadays,it has been closely studied in the research field of natural language processing(NLP) due to its wide real applications.As a result,many supervised machine learning classification approaches have been applied to this task.In this paper,we research on four classification approaches and propose a new combination method based on stacking to combine these four approaches.Experimental results show that our combination method achieves better performances than the best single one.Therefore,this combination method can avoid selecting a suitable classification approach according to different domains.