An efficient target recognition method for large scale data is proposed in this paper

which is based on self-organizing map (SOM) neural network and support vector machines (SVMs).The target data set is divided into clusters by SOM first.Then

the support vector machines are applied to classify targets.The new method is used to classify the complex XOR problem

Iris and Appendicitis data

and the experimental results show that the new method can obtain better recognition results for the complex pattern classification of large scale data

and the trainning time is shorter than that by using the support vector machine method only.