The invention provides a network traffic classification method. The method comprises the steps that (1) a network traffic behavior characteristic set is extracted; (2) a classifier model is obtained, the behavior characteristic set is input in a classifier, classification training is carried out, and corresponding parameters are obtained; (3) the performance of the classifier is evaluated and optimized. According to the method, a non-supervision algorithm and a supervision algorithm in a machine learning method are combined to carry out classification. By means of the combination of the non-supervision algorithm and the supervision algorithm, under the premise that a high classification accuracy rate is ensured, the time and memory expenditure of a system is reduced, and the classification efficiency is improved. A clustering algorithm is improved, the clustering accuracy rate is increased, and therefore the overall performance is improved.