It is a challenging topic to develop an efficient algorithm for large scale classification problems in many applications of machine learning.In this paper,a hierarchical clustering and fixedlayer local learning (HCFLL) based support vector machine(SVM) algorithm is proposed to deal with this problem.Firstly,HCFLL hierarchically clusters a given dataset into a modified clustering feature tree based on the ideas of unsupervised clustering and supervised clustering.Then it locally trains SVM on each labeled subtree at a fixed-layer of the tree.The experimental results show that compared with the existing popular algorithms such as core vector machine and decision-tree support vector machine,HCFLL can significantly improve the training and testing speeds with comparable testing accuracy.