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SerializationDemo
- These instances, whenmapped to an N-dimensional space, represent a core set that can be used to construct an approximation to theminimumenclosing ball. Solving the SVMlearning problem on these core sets can produce a good approximation solution i
SVM_FACE
- 基于支持向量机的人脸检测训练集增强算法实现。根据支持向量机(support vector machine，简称SVM)~ ，对基于边界的分类算"~(geometric approach)~ 言，类别边界附近的样本通常比其他样本包含有更多的分类信息．基于这一基本思路，以人脸检测问题为例．探讨了 对给定训练样本集进行边界增强的问题，并为此而提出了一种基于支持向量机和改进的非线性精简集算法 IRS(improved reduced set)的训练集边界样本增强算法，用以扩大-91l练集并改
lasvm-source-1.1.tar
- LASVM is an approximate SVM solver that uses online approximation. It reaches accuracies similar to that of a real SVM after performing a single sequential pass through the training examples.
LS-SVMLab-v1.7(R2006a-R2009a)
- 支持向量机SVM(Support Vector Machine)它在解决小样本、非线性及高维模式识别中表现出许多特有的优势，并能够推广应用到函数拟合等其他机器学习问题中-Support Vector Machine SVM (Support Vector Machine) it addresses the small sample, nonlinear and high dimensional pattern recognition performance of many unique adva
SVM-function-available
- 可以实现SVM函数曲线拟合，支持向量机曲线逼近，多类分类等等强大功能，无需修改源程序，直接可用-The SVM function curve fitting, support vector machines curve approximation, powerful multi-class classification, etc., without modifying the source code directly available
SVM
- SVM工具箱，各种分类及拟合算法,使用起来很方便。-SVM tools for classification and approximation