搜索资源列表
oao
- 多分类问题的支持向量机源程序一对一方法 绝对可以运行-Multi-class SVM using One-Against-One decompositionoao
svdd
- 超球面支持向量机,一种构建超球面来进行分类的单类svm -Ultra-spherical support vector machine, a super-spherical to build a single-category classification SVM
LS-SVMlab1.5aw
- 一种基于matlab的支持向量机小例子,用于预测,LS-A matlab-based support vector machine small example for the prediction, LS
SVR
- 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
svm-guide
- 介绍支持向量机工具箱的 使用-svn guide
KPCA_SVM_Train
- 核主元分析和支持向量机结合的故障诊断方法-KPCA and SVM fault diagnosis method combining
libsvm-mat-2.88-1
- 最小二乘支持向量机工具包,内嵌在Matlab环境中运行-LS—SVM tools
95302935SVM-KMExample
- 支持向量机,matlab工具集。涵盖关于支持向量机的各种主要算法实现。-Support Vector Machines, matlab tools. Support Vector Machine on the cover of the main algorithm.
SVM
- MATLAB写的支持向量机的一些程序,希望对大家的学习有用。-MATLAB Support Vector Machine to write some of the procedures, we hope to learn useful.
MATLAB_svm
- 关于支持向量机的MATLAB程序,用于模式识别-On the MATLAB support vector machine procedures for pattern recognition
fsvm
- 模糊支持向量机向量机的国外文章,可得到更精确的仿真图形-Fuzzy Support Vector Machine SVM foreign article can be a more accurate simulation graphics
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
GASVM
- 用遗传算法改进支持向量机的算法,虽然比较老点,但是还是很有用。-This program is about SVM which is improved by PSO.I think it is a good algorithm
SVM
- 对于初学者是一篇很好的学习支持向量机的英文文章-For beginners, a very good learning support vector machines in English articles
svm
- 用MATLAB编写的svm源程序,可以实现支持向量机,用于特征分类或提取-MATLAB source code written using svm, support vector machine can be achieved for feature classification or extraction
svm-cailiao
- 支持向量机的原理、应用。支持向量机的算法、综述、核函数的定义等-Support vector machine principle, application. Support vector machine algorithm, summarized the definition of kernel function
LSSVMNARX
- 基于最小二乘支持向量机的NARX模型辨识,用于设备故障诊断-program based on LS-SVM NARX for diagnosis
LS_SVMlab
- 支持向量机的MATlab工具包,很有用,也很复杂,没有功底的,就别下了-SVM MATlab kit, useful, and very complex, there is no foundation for, do not down
SVM_Short-term-Load-Forecasting
- 优秀论文及配套源码。首先阐述了负荷预测的应用研究现状,概括了负荷预测的特点及其影响因素,归纳了短期负荷预测的常用方法,并分析了各种方法的优劣;接着介绍了作为支持向量机(SVM)理论基础的统计学习理论和SVM的原理,推导了SVM回归模型;本文采用最小二乘支持向量机(LSSVM)模型,根据浙江台州某地区的历史负荷数据和气象数据,分析影响预测的各种因素,总结了负荷变化的规律性,对历史负荷数据中的“异常数据”进行修正,对负荷预测中要考虑的相关因素进行了归一化处理。LSSVM中的两个参数对模型有很大影响,
KPCA_SVM_Train-jkk
- 主成分、支持向量机分类,matlab编写的-Principal component, support vector machine classification, matlab prepared