留一模型选择法leave-one-out model selection，适合支持向量机分类和回归时进行参数选择。-looms uses a slightly modified BSVM to perform model selection on binary classification problems. Currently the RBF kernel is supported.

在libsvm平台下，用RBF核函数和polynomial多项式核函数结合，形成新的混合核函数，求验证其正确性-libsvm kernel of RBF and ploynomial

使用支持向量数据描述，使用RBF核。利用被检测数据画出一个散点图。-Using support vector data descr iption, use the RBF kernel. Use test data to draw a scatter plot is.

This project is a C++ implementation of a second-order Maclaurin series approximation of LIBSVM models using an RBF kernel. This approximation greatly increases prediction speed for models with many support vectors but in few dimensions.