Deep Kernel Mapping Support Vector Machines Based on Multi-layer Perceptron

To improve the performance of support vector machines (SVMs), from the deep learning’s point of view, a kernel learning method was studied and a deep kernel mapping support vector machine (DKMSVM) was proposed based on multi-layer perceptron together with the corresponding learning algorithm. Firstly, a kernel mapping from the original input space to a proper dimensional space through a multilayer perceptron instead of a traditional kernel function was researched in this model. Then a SVM was used to classify in the proper dimensional space without kernel tricks. Experimental results demonstrate the effectiveness of DKMSVM.