说明：  支持向量机方法中也存在着一些亟待解决的问题，主要包括：如何用支持向量机更有效的解决多类分类问题，如何解决支持向量机二次规划过程中存在的瓶颈问题、如何确定核函数以及最优的核参数以保证算法的有效性等。
(Support vector machine (SVM) method also exist some problems to be solved, mainly includes: how to use support vector machine (SVM) is more effective to solve many class classification problem, support vector machines (SVM) is how to solve quadratic programming bottleneck problems existing in the process, how to determine the kernel function and the optimal kernel parameters to ensure the effectiveness of the algorithm and so on.)