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matlab_image.matlab图像预处理
- matlab图像预处理，包括灰度化，对数变换，直方图均衡化，线性平滑滤波，中值滤波，自适应滤波，图像锐化，图像二值化，各类边缘检测算子等等,matlab image preprocessing, including gray-scale and logarithmic transformation, histogram equalization, linear filtering, median filtering, adaptive filtering, image sharpening, i
stprtool.rar
- 统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含： 1，Analysis of linear discriminant function 2，Feature extraction: Linear Discriminant Analysis 3，Probability distribution estimation and clustering 4，Support Vector and other Kernel Machines,
SVM-classifier
- 用matlab实现非线性支持向量机分类器对多类进行分类。-Using matlab to achieve non-linear support vector machine classifier for multi-class classification.
SVM_lzb1p0
- svm（支持向量机）能进行分类。有不同的核函数，如线性，多项式等-svm (support vector machine) can be classified. There are different kernel functions, such as linear, polynomial, etc.
lpsvr
- 一个我自己编写的求解线性支持向量机的matlab代码-I have prepared a solution of linear SVM matlab code
file
- 利用matlab开发平台和相关的SVM优化工具箱,及OAO,OAA,BSVM2算法模型,设计改进并实现非线性的模式分类实验模型系统.-Matlab use development platform and related optimization toolbox of SVM, and OAO, OAA, BSVM2 algorithm model, designed to improve and to achieve non-linear model of the pattern classi
libsvm-2.89
- 是一種線性方成的分類器。SVM透過統計的方式將雜亂的資料以NN的方式分成兩類，以便處理。LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, and L1-loss linear SVM. -Main features of LIBLINEA
LinearSVC
- Construct a linear SVM classifier from the training Samples and Labels
non-linearSVMmulti-classification
- 转发一个可视化的非线性支持向量机多分类源码，比较实用易学，值得进一步深入开发。-non-linear SVM multi-classification
SVM
- In this paper, we show how support vector machine (SVM) can be employed as a powerful tool for $k$-nearest neighbor (kNN) classifier. A novel multi-class dimensionality reduction approach, Discriminant Analysis via Support Vectors (SVDA), is in
SVMnonlinforASI
- SVM PCA (Principal Component Analysis) algorithm has been widely used in engineering and science research, This report mainly from the PCA and the basic structure of the basic tenets of its research, Conventional PCA algorithm used mainly linear algo
SVMClassificationFunction
- this a matlab coding of svm classification function. when inputing training samples, training labels, testing samples, testing labels, and two parameters, the classification result is obtained. linear svm and nonlinear svm can be selected.-this
svm
- 线性SVM算法设计分类器，对一组数据进行分类-Linear SVM classifier algorithm on a set of data classification
svm
- SVM方法的基本思想是：定义最优线性超平面，并把寻找最优线性超平面的算法归结为求解一个凸规划问题。进而基于Mercer核展开定理，通过非线性映射φ，把样本空间映射到一个高维乃至于无穷维的特征空间（Hilbert空间），使在特征空间中可以应用线性学习机的方法解决样本空间中的高度非线性分类和回归等问题。svm 程序，即支持向量机的代码。-The basic idea of SVM method are: the definition of the optimal linear hyperplane,
Matlab-svm
- 支持向量机是一种新的回归方法，特别适用于非线性，改程序实现了支持向量机非线性回归-surport vector machine to non-linear regression
CODE
- 1.GeometricContext文件是完成图片中几何方向目标分类。 参考文献《Automatic Photo Pop-up》Hoiem 2005 2 GrabCut文件是完成图像中目标交互式分割 参考文献《“GrabCut” — Interactive Foreground Extraction using Iterated Graph Cuts》 C. Rother 2004 3 HOG文件是自己编写的根据HOG特征检测行人的matlab代码 4 虹膜识别程序
Matlab-svm-BP-compare
- 支持向量机和BP神经网络虽然都可以用来做非线性回归，但它们所基于的理论基础不同，回归的机理也不相同。支持向量机基于结构风险最小化理论，普遍认为其泛化能力要比神经网络的强。为了验证这种观点，本文编写了支持向量机非线性回归的通用Matlab程序和基于神经网络工具箱的BP神经网络仿真模块，仿真结果证实，支持向量机做非线性回归不仅泛化能力强于BP网络，而且能避免神经网络的固有缺陷——训练结果不稳定。-SVM and BP neural networks, although non-linear regr
nonlinear-svm-code
- svm线性和非线性的处理源代码。加了很多说明，希望对你有帮助-SVM linear and nonlinear processing the source code. Add a lot of shows, the hope is helpful to you
libsvm-3.20
- 根据训练数据，使用SVMlib 学习TrainLetter.txt的linear SVM models, 进而预测测试数据TestLetter.txt的分类结果(According to the training data, the TrainLetter.txt linear SVM models is learned by using SVMlib, and then the classification results of the test data TestLetter.txt are