Summary: An adaptive support vector machine integrated method was proposed based on nearest neighbor classification accuracy. For the classified samples, the effective neighborhood on the fuzzy feature space set was determined automatically by using the improved FCM and fuzzy nearness degree search algorithm. Based on classification accuracy and threshold, the model could dynamically select a set of optimal individual classifier to integrate. Experimental results show that the proposed method can improve the classification performance and shorten the discrimination time.