搜索资源列表
8888
- 基于回归理论分析的支持向量代码及m代码-Based on support vector regression analysis code and m code
svmroc
- 支持向量有一种方法是分类法，另一种是回归法-supported vector machine
SVR
- 支持向量机的回归拟合——混凝土抗压强度预测 专门针对小样本问题而提出，在有限样本的情况下获得最优解。-The return of the support vector machine fitting, concrete compressive strength prediction Specifically targeted at small sample problem and put forward, in limited sample gain the optimal solution
chapter14
- 支持向量机神经网络的回归预测分析 以上证指数预测为例-Regression analysis of support vector machine neural network prediction for example Shanghai Composite Index
FOASVR
- FOASVR算法实现，用于支持向量机回归的实现-FOASVR algorithm implementation，used to apply the SVR
libsvm-3.1(Chen)
- 支持向量机的分类与回归，可以实现样本数据的分类和数据的趋势预测-SVM classfiction and regression
SVM-KM
- K-近邻支持向量机回归，工具箱，全程Matlab-K-Support Vector machine Matlab， This function process the SVM regression model using a linear epsilon insensitive cost
LS-SVMLab-v1.7(R2006a-R2009a)
- matlab中的ls-svm工具包，是最小二乘支持向量机算法，可用于解决非线性的回归问题。-ls-svm tool in the Matlab package, least squares support vector machine algorithm can be used to solve nonlinear regression problems.
libsvm-3.12
- matlab中的libsvm工具包，是smo支持向量机算法，可用于解决非线性的回归问题。区别于最小二乘支持向量机。-Matlab libsvm Kit is to smo support vector machine algorithm that can be used to solve nonlinear regression problems. Different from the least squares support vector machine.
program-of-support-vector-machine
- matlab中的标准svm程序源码，用于解决线性的回归问题，不能用于解决非线性，区别于最小二乘支持向量机。-svm program source code, standard Matlab is used to solve linear regression problems, can not be used to solve nonlinear, different from the least squares support vector machine.
svm_c
- 支持向量机，做混凝土回归预测的。十分好用的程序-Support vector machines for concrete regression prediction. Very easy to use program
SVM_GUI
- 支持向量机进行分类和回归的界面，非常好用-Support vector machines for classification and regression interface, very easy to
main_svc
- 在matlab中编写关于支持向量机进行回归分析的源代码M文件。-In matlab to write about support vector machine for regression analysis of source code M file.
Ssvmm_light_mV
- SVM Light的多分类源代码，尤其是可用来做文本分类。SVM（支持向量机机）方法是目前已知的最优秀的分类方法之一。SVM不仅能用来分类，也能用来做回归。 -The SVM Light classification of source code, in particular, used to make text classification. SVM (support vector machine machine) method is one of the currently known
svm-struct
- 支持向量机结构回归算法（svm-struct），一种新的回归方法，有文献和PPT，方便学习。-Support the structural regression algorithm vector machine (svm-struct), a new regression method, literature and PPT to facilitate learning.
SVMNR
- 分区支持向量机源代码，可进行分区支持向量机回归-Partition support vector machine source code, can be the the partition support vector machine regression
ZCXLJ
- 支持向量机和BP神经网络都可以用来做非线性回归拟合，但它们的原理是不相同的，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。大量仿真证实，支持向量机的泛化能力强于BP网络，而且能避免神经网络的固有缺陷——训练结果不稳定。本源码可以用于线性回归、非线性回归、非线性函数拟合、数据建模、预测、分类等多种应用场合-Support vector machines and BP neural network can be used for non-linear regression f
arsvmModel_shm
- 运用matlab编程实现自回归支持向量机算法-autogressive support vector machine
LS_SVMlab
- 最小二乘支持向量机MATLAB实现源代码，可以用于模式识别以及回归-Least squares support vector machine MATLAB source code, can be used for pattern recognition and regression
svmprogram
- SNM支持向量机预测，回归分析,数据预测。实验验证-SNM prediction, support vector machine regression analysis