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Description: 支持向量机方面的，是Steve R Runn的svm工具箱的说明文件，-Aspects of support vector machine is the Steve R Runn documentation svm toolbox, huh, huh
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Size: 124928 |
Author: liuzhonghua |
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Description: 易于使用、快速有效的通用SVM 软件包，可以解决分类问题（包括C- SVC、
n - SVC ）、回归问题（包括e - SVR、n - SVR ）以及分布估计（one-class-SVM
-Easy to use, fast and effective generic SVM software package can solve the classification problems (including the C-SVC, n- SVC), regression (including e- SVR, n- SVR) as well as the distribution of estimates (one-class-SVM
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Size: 3941376 |
Author: yuanmin |
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Description: LIBSVM 是台湾大学林智仁(Chih-Jen Lin)博士等开发设计的一个操作简单、易于使用、快速有效的通用SVM 软件包，可以解决分类问题（包括C- SVC、n - SVC ）、回归问题（包括e - SVR、n - SVR ）以及分布估计（one-class-SVM ）等问题，提供了线性、多项式、径向基和S形函数四种常用的核函数供选择，可以有效地解决多类问题、交叉验证选择参数、对不平衡样本加权、多类问题的概率估计等。
2.89版本是09年刚更新的一个版本。-LIBSVM
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Size: 566272 |
Author: woyaofei |
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Description: SVM 软件包，可以解决分类问题（包括C- SVC、n - SVC ）、回归问题（包括e - SVR、n - SVR ）以及分布估计（one-class-SVM ）等问题-SVM software package can solve the classification problems (including the C-SVC, n- SVC), regression (including e- SVR, n- SVR) as well as the distribution of estimates (one-class-SVM) and other issues
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Size: 32768 |
Author: hanzeyu |
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Description: SVR程序,直接用就可以了,没有错误,其中还有一些变量需再编程序算,如:MSE-SVR procedure can be used directly and there is no mistake, there are some variables which should be subject to the procedures for counting, such as: MSE
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Size: 9216 |
Author: shihuizhuo |
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Description: SVR程序,直接用就可以了,没有错误,其中还有一些变量需再编程序算,如:MSE-SVR procedure can be used directly and there is no mistake, there are some variables which should be subject to the procedures for counting, such as: MSE
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Size: 10240 |
Author: shihuizhuo |
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Description: SVR的一些例子,对初学者来说,非常有用,可以照着例子学,这样上手比较快-Some examples of SVR for beginners, very useful, you can follow example of science, this relatively fast start
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Size: 3072 |
Author: shihuizhuo |
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Description: SVR的一些例子,对初学者来说,非常有用,可以照着例子学,这样上手比较快-Some examples of SVR for beginners, very useful, you can follow example of science, this relatively fast start
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Size: 2048 |
Author: shihuizhuo |
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Description: 在线向量回归分析，有包涵一个例子和内定函数等-On-line vector regression analysis, there is an example of indulgence and unofficially functions, etc.
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Size: 31744 |
Author: 李強 |
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Description: Support vector regression code
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Size: 31744 |
Author: xgq |
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Description: 为了选择神经网络的最好结构以及增强模型的推广能力，提出一种自适应支持向量回归神经网络(SVR—NN)。SVR—NN 用支持向量回归(SVR)方法获得网络的初始结构和权值， 白适应地生
成网络隐层结点，然后用基于退火过程的鲁棒学习算法更新网络结点疹教和权 主。 SVR—NN有很
好的收敛性和鲁棒性，能抑制由于数据异常和参数选择不当所导致的“过拟合，’现象。将SVR—NN
应用到时间序列预测上。结果表明，SVR．NN预测模型能精确地预测混沌时间序列，具有很好的
理论和应用价值。-Abstract：To select the‘best’structure of the neural networks and enhance the generalization ability of models．a support
vector regression neural networks fSVR-NN)was proposed．Firstly，support vector regression approach was applied to
determine initial structure and initial weights of SVR．NN SO that the number of hidden layer nodes can be constructed
adaptively based on support vectors．Furthermore，an annealing robust learning algorithm was further presented to fine
tune the hidden node parameters and weights of SVR一ⅣM The adaptive SVR．NN has faSt convergence speed and robust
capability．and it can also suppress the ‘orerfitting’phenomena when the train data ncludes outliers．The adaptive
SVR．NN was then applied to time series prediction．Experimental results show that the adaptive SVR．ⅣⅣ can accurately
predict chaotic time series，and it iS valuable in both theory and application aspects．
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Size: 316416 |
Author: 11 |
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Description: 要建立一个有效的支持向量回归(SVR)模型，支持向量回归的3个参数c，y，占丛须预先设定。提出一种新型的遗传算
法一智能遗传算法(IGA)对支持向量回归进行参数调节，以达到寻找最优参数的目的，然后和支持向量回归结合得到一种新的
IGASVR模型，并应用于城市人口预测。最后，将提出的方法与标准SVR模型和BP神经网络模型进行比较，所得结果表明，该模
型训练速度快，并且有较高预测精度，是一种有效的人口预测方法。-To build an effective SVR model，SVR’8 parameters must be set carefully．This study proposes a novel approach，
known ag IGASVR。which searches for SVR’s optimal parameters using intelligent genetic algorithms，and then adopts the optimal
parameters to construct the SVR models．Finally we apply IGASVR tO forecast population．The experimental results demonstrates
that IGASVR are better than standard SVR and BP neural-network．IGASVR model is an effective approach which has faster
speed of training and higher precision．
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Size: 372736 |
Author: 11 |
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Description: 统计学习理论中提出的支撑向量机回归(SVR)遵循了结构风险最小化原则,从而避免了一味追求经验风险最小化带来的弊端-Statistical learning theory proposed by the support vector machine regression (SVR) to follow the structural risk minimization principle, thus avoiding the blind pursuit of Empirical Risk Minimization the evils of
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Size: 3072 |
Author: han fei |
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Description: 基于遗传算法的支持向量回归机参数选取，针对支持向量回归机( support vector regression , SVR) 的参数选择问题,提出了基于遗传算法的
SVR 参数自动确定方法。分-Based on genetic algorithm parameter selection of Support Vector Regression
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Size: 235520 |
Author: 王明 |
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Description: 支持向量机回归在股市预测中的应用,有论文和大量仿真曲线说明-the application of SVR in the Stock prediction
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Size: 322560 |
Author: 曹志民 |
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Description: 79419096svr一维支持向量机回归以及二维支持向量机回归-79419096svr one-dimensional support vector regression and two-dimensional support vector regression
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Size: 235520 |
Author: myzone |
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Description: svm 的matlab程序,是最基本的svm形式-the sourse of svm,it is the basic styple
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Size: 2048 |
Author: 赵爽 |
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Description: 一位意大利博士编写的关于online SVR的工具箱，对我启发很大。附加了Powell法优化工具-a matlab toolbox about online SVR and Powell
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Size: 33792 |
Author: yan |
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Description: -s svm类型：SVM设置类型(默认0)
0 -- C-SVC
1 --v-SVC
2 – 一类SVM
3 -- e -SVR
4 -- v-SVR
-t 核函数类型：核函数设置类型(默认2)
0 – 线性：u v
1 – 多项式：(r*u v + coef0)^degree
2 – RBF函数：exp(-r|u-v|^2)
3 –sigmoid：tanh(r*u v + coef0)
-d degree：核函数中的degree设置(针对多项式核函数)(默认3)
-g r(gama)：核函数中的gamma函数设置(针对多项式/rbf/sigmoid核函数)(默认1/ k)
-r coef0：核函数中的coef0设置(针对多项式/sigmoid核函数)((默认0)
-c cost：设置C-SVC，e -SVR和v-SVR的参数(损失函数)(默认1)
-n nu：设置v-SVC，一类SVM和v- SVR的参数(默认0.5)
-p p：设置e -SVR 中损失函数p的值(默认0.1)
-m cachesize：设置cache内存大小，以MB为单位(默认40)
-e eps：设置允许的终止判据(默认0.001)
-h shrinking：是否使用启发式，0或1(默认1)
-wi weight：设置第几类的参数C为weight*C(C-SVC中的C)(默认1)
-v n: n-fold交互检验模式，n为fold的个数，必须大于等于2--s svm_type : set type of SVM (default 0)
0-- C-SVC
1-- nu-SVC
2-- one-class SVM
3-- epsilon-SVR
4-- nu-SVR
-t kernel_type : set type of kernel function (default 2)
0-- linear: u *v
1-- polynomial: (gamma*u *v+ coef0)^degree
2-- radial basis function: exp(-gamma*|u-v|^2)
3-- sigmoid: tanh(gamma*u *v+ coef0)
4-- precomputed kernel (kernel values in training_instance_matrix)
-d degree : set degree in kernel function (default 3)
-g gamma : set gamma in kernel function (default 1/k)
-r coef0 : set coef0 in kernel function (default 0)
-c cost : set the parameter C of C-SVC, epsilon-SVR, and nu-SVR (default 1)
-n nu : set the parameter nu of nu-SVC, one-class SVM, and nu-SVR (default 0.5)
-p epsilon : set the epsilon in loss function of epsilon-SVR (default 0.1)
-m cachesize : set cache memory size in MB (default 100)
-e epsilon : set tolerance of termination criterion (default 0.001)
-h shrinking: whether to use the shrinking heuristics, 0 or 1 (default 1)
-b
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Size: 17408 |
Author: little863 |
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Description: 台湾林智仁编写的支持向量机开源程序，可用于分类（C-SVC，nu-SVC，one-class SVM）和回归（epsilon-SVR，nu-SVR）。这是最新版本3.0。-Libsvm3.0 is a simple, easy-to-use, and efficient software for SVM
classification and regression. It solves C-SVM classification, nu-SVM
classification, one-class-SVM, epsilon-SVM regression, and nu-SVM
regression. It also provides an automatic model selection tool for
C-SVM classification.
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Size: 576512 |
Author: 大木木 |
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