多类分问题通常采用多个标准的二分类支持向量机来求解,在这种情况下,需要解多个二次规划问题.为了简化多类分类问题带来的计算复杂性,本文根据一类分类思想提出一种多类分类算法,所给算法通过引入核函数能够独立地对每一类样本形成一个紧致的优化区域,从而达到分类的目的.人工及实际数据库的仿真实验表明所给算法在保持良好的分类精度条件下,能有效降低程序的运行时间. In this case, multiple quadratic programming problems need to be solved.In order to simplify the computational complexity caused by the multi-class classification problems, this paper presents a new class of classification problems based on a class of The classification idea proposes a multi-class classification algorithm, and the proposed algorithm can form a compact optimization region for each type of samples independently by introducing kernel functions, so as to achieve the purpose of classification.The artificial and actual database simulation results show that the proposed algorithm Under the condition of maintaining good classification accuracy, it can effectively reduce the running time of the program.