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svm_c++
- 应用c＋＋实现的svm向量机分类算法，相信对svm感兴趣的朋友有帮助！-c + + applications to achieve the svm vector machine classification algorithm, I believe right svm interested friends!
Dev.tar
- MSVM，svm的多分类问题实现，实现语言为c
DRAP
- 该系统能取得与SVM相当的精度，但运行速度却远远快于SVM。目前，该系统已在大规模高速数据流过滤中得到应用。在普通PC上它的过滤(分类)速度可以超过4M/秒。若用10k来估计一篇文本的长度，那么本系统每秒钟可以过滤(分类)约400篇文本。本系统的核心部分采用C++编码，界面采用VB开发平台。安装包是在VB6.0环境下使用VB自身的打包工具打包而成。安装后即可使用。
libsvm-2.84-string
- MATLAB版的SVM，使用相对于C来比较的方便，可以试一试
svm python
- Put simply, SVMpython is SVMstruct, except that all of the C API functions that the user normally has to implement (except those dealing with C specific problems) instead call a function of the same name in a Python module. You can write an SVMstruct
SVM
- SVM usful totorial C-C-SVM usful totorial C-C++
psosvm
- pso优化svm的程序。C版。可以用于一些预测性问题-pso optimization svm
lssvm_demo.m
- LS-SVM Leave-One-Out Cross-Validation Demo G. C. Cawley, "Leave-one-out cross-validation based model selection criteria for weighted LS-SVMs", Proceedings of the International Joint Conference on Neural Networks (IJCNN-2006), pages 1661-1668, Vanco
SVM
- 基于SVM的回归预测——上证指数开盘指数预测,包括数据的提取和预处理，选择回归预测分析最佳的SVM参数c&g，利用回归预测分析最佳的参数进行SVM网络训练-SVM-Based Forecasting
chapter15_0
- svm 的参数优化，利用交叉验证法选择最优参数c g，最终提高训练集的分类准确率,更好的提高分类器性能-Svm parameter optimization, the use of cross-validation method to the optimal parameter c g, and ultimately improve the training set classification accuracy，better improve the classifier performan
chapter15_PSO
- svm 的参数优化，利用pso(粒子群优化算法)选择最优参数c g，最终提高训练集的分类准确率，更好的提高分类器性能-Svm parameter optimization, the use of pso (particle swarm optimization algorithm) to the optimal parameter c g, and ultimately improve the training set classification accuracy, better impr
chapter15_GA
- svm 的参数优化，利用ga(遗传优化算法)选择最优参数c g，最终提高训练集的分类准确率，更好的提高分类器性能-Svm parameter optimization, the use of ga (genetic optimization algorithm) to the optimal parameter c g, and ultimately improve the accuracy of the training set classification, better improve
gaSVMcgForClass
- svm 的参数优化，利用ga(遗传优化算法)选择最优参数c g，最终提高训练集的分类准确率，更好的提高分类器性能,这是ga的功能函数源码-Svm parameter optimization, the use of ga (genetic optimization algorithm) to the optimal parameter c g, and ultimately improve the training set classification accuracy, better imp