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ordreg
- 基于MATLAB编写的SVM多分类算法程序
SVM
- 支持向量机用于多分类问题的程序,可以较好地运行.
svm
- 这是我自己编的一个基于svm的多分类程序，但并不是很成功，还望看了给予指点。
基于svm的分类器
- c++ 开发的svm分类器，功能不错，支持多类，多标签分类。使用方便，欢迎下载！
MC-SVM1.0.1
- 多类支持向量分类机，可避免两类支持向量分类机的相关缺点，实现多类分类-Multi-Class Support Vector Machine, we can avoid two kinds of support vector machine classification of defects, multi-category classification
svmlight_multiclass
- windows操作系统下的支持向量机算法实现工具包，支持多类别分类，功能强大！-windows operating system support vector machine algorithm tool kit, support multi-category classification, powerful!
lasvm-source
- 用C语言实现的最新且最快的SVM源码,可用于解决多类分类问题-C language of the latest and fastest source of SVM can be used to solve the multi-category classification
SVM_luzhenbo
- 1、工具箱：LS_SVMlab Classification_LS_SVMlab.m - 多类分类 Regression_LS_SVMlab.m - 函数拟合 2、工具箱：OSU_SVM3.00 Classification_OSU_SVM.m - 多类分类 3、工具箱：stprtool\svm Classification_stprtool.m - 多类分类 4、工具箱：SVM_Steve
libsvm-weight-2.81
- 一种基于局部密度比权重设置模型的加权支持向量回归模型来单步求解多分类问题：该方法先分别对类样本中每类样本利用局部密度比权重设置模型求出每个样本的权重隶属因子,然后运用加权lib支持向量回归算法对所有样本进行训练,获得回归分类器,希望对大家有用!-Based on local density than the right to re-set model of weighted support vector regression model
four Toolbox for SVM
- 这里实现了基于四种SVM工具箱的分类与回归算法: 1、工具箱：LS_SVMlab Classification_LS_SVMlab.m - 多类分类 Regression_LS_SVMlab.m - 函数拟合 2、工具箱：OSU_SVM3.00 Classification_OSU_SVM.m - 多类分类 3、工具箱：stprtool\svm Classification_stprtool
SVM
- 已调的SVM多分类的MATLAB代码，包括原始数据，很好用的-Modulated SVM multi-classification MATLAB code, including raw data, well used
SVM-multiple-class
- 关于matlab的多分类问题的几篇文章，对于学习matlab 中的svm 多分类问题有帮助-Multi-classification on matlab several articles for learning in matlab svm multi-classification helpful
SVM
- SVM多分类算法的一些程序，有很多种类型，包括经典的四种工具箱，还有代价敏感支持向量机，超球面支持向量机等-Some programs about SVM multi-classification algorithm, there are many types, including the classic four toolbox, as well as the price-sensitive support vector machin
SVMRFE.m
- 基于RFE特征选择方法的多分类特征排序，Matlab平台(Multi class feature ranking based on RFE method)
SVM
- SVM图片多分类，包含一组示例图片以及程序，程序有相应的注释，(Multi classification of SVM pictures,Contains a set of sample pictures and programs ,The program has a corresponding annotation .)
前上右左手向有摆动svm算法85.333%
- 使用matlab libsvm 工具箱能够实现多分类任务(LIBSVM classification)
20171211留档
- 利用SVM对制备的样本进行三分类，对图像进行三角形匹配，模板匹配(SVM was used to classify the samples in three categories. Triangle matching and template matching were applied to the images.)
libsvm-mat-2[1].89-3[FarutoUltimate3.0Mcode]
- 一般的支持向量机只支持二分类，使用libsvm可以实现多分类，原理也是基于二分类，然后在使用投票机制，经测验，libsvm的分类精度可达85%以上(Multi class supported by libsvm,after testing, the classification accuracy can reach 85%.)
mtsvm
- 多分类孪生支持向量机,主体是-1 1的2分类孪生支持向量机，采用onevsone改编成多分类的孪生支持向量机(multi classification twin support vector machine, kernel code is binary-classification twin support vector machine ,constructed it as a multi classification twin sup
SVM
- 利用三次二分类SVM实现三分类SVM，可以用自己的数据，完美运行。(Using the three-category SVM to implement the three-class SVM, you can use your own data to run perfectly.)