搜索资源列表
activities_of_the_shape_model
- 基于支持向量机分类器的活动形状模型。学术论文。-Support vector machine classifier based on the activities of the shape model. Papers.
SVM_lzb1p0
- 关于matlab支持向量机的程序，学习支持向量机的人可以看看。-On support vector machine matlab program, learning support vector machines can see.
SVM-KMExample
- 支持向量机SVM和核函数的matlab程序集-SVM matlab
OSU_SVM3.00
- 支持向量机的相关程序：包括了支持向量机在图像处理中的多个用处-Support vector machine procedures: including support vector machines in a number of useful image processing
SVM_lzb1p2015
- matlab工具箱，SVM。。。支持向量基-matlab toolbox, SVM. . . Support vector-based
USPS2Bsvm
- 自己用支持向量机编的一个小程序，很好的实现了分类-Their series with support vector machine is a small program achieved very good classification
SVMNN
- 使用支持向量机SVM神经网络分类数据的预测-the prediction of data classification by SVM neural network
svmTrain2
- 局部化的支持向量机（LSVR）训练内核函数-function for LSVR(localized support vector regression) training
SVM
- SVM基础资料,关于核函数的分类及可支持向量机的一些资料-SVM based on information about the kernel function support vector machine classification and may some of the information
SVM_lzb1p0
- 支持向量机代码，和Matlab上自带的代码不一样啊-Support vector machine code
461518386Yale_PCASVM
- 程序包实现了几个常用的模式识别分类器算法，包括K近邻分类器KNN、线性判别方程LDF分类器、二次判别方程QDF分类器、RDA规则判别分析分类器、MQDF改进二次判别方程分类器、SVM支持向量机分类器。-svm apply to fenlei
svm
- 支持向量机可以对样本进行的分类，具有很好的泛化能及，并且可以解决小样本学习问题，在学习过程中避免出现局部最优解-Support vector machine classification of samples can have very good generalization can be and, and can solve the small sample learning problems, in the learning process to avoid local optima
SVM
- 支持向量机辅助程序，可以帮助完成支持向量机的计算过程-Support vector machine aids, can help to complete the calculation process SVM
SVMinDataMine
- 支持向量机的一本入门书籍《数据挖掘中的新方法：支持向量机》。-A support vector machine entry books, " A new method of data mining: support vector machines."
incremental
- Gert Cauwenberghs写的一个增量型支持向量机，非常有用的-Gert Cauwenberghs wrote a incremental support vector machive. It is very useful for learning about it.
svm1
- 支持向量机的学习，简单但实用，推荐给各位哦-Studying supporting vector machine, is simple but pragmatic, recommendation is softly chanted by everybody
SVR
- SVR 支持向量回归机，这是SVM的一种拓展类型，可以有效的完成非线性拟合-SVR support vector regression, which is an expanding type of SVM, can effectively complete the nonlinear fitting
SVM
- 支持向量机是Cortes和Vapnik于1995年首先提出的，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 is Cortes and Vapnik in 1995 first proposed, it solve the small sample, nonlinear and high dimensional pattern recognition performance in many
Fromneuralnetwork_to_supportvectormachines
- 从神经网络到支持向量机 上中下总共为 三部-From neural networks to support vector machines in a total of three under
LIBSVM_ALibrary
- LIBSVM - A Library for Support Vector Machines 支持向量机原理介绍以及 libsvm 的使用方法-LIBSVM- A Library for Support Vector Machines Support vector machine introduction and use of libsvm