搜索资源列表
winsvm
- 这是一个实现文本分类svm的程序，可以手动修改参数
LS
- 试验模态分析的时域识别方法的一种，可以识别出信号的模态参数，固有频率阻尼比振型系数，-Experimental modal analysis of a time-domain identification method that can identify the signal modal parameters, natural frequency mode of vibration damping ratio coefficient,
svmfenlei
- 利用支持向量机实现非线性分类，通过调节参数改变分类个数-Nonlinear SVM classification, change classification number by adjusting the parameters
GridSearch_svm_cg
- 支持向量机参数网格寻优算法 a toolbox with implements for support vector machines based on libsvm-svm gridsearch
chapter13_GA
- 对最小二乘支持向量机的核函数进行参数优化，最后得到分类更加准确的分类器-For least squares support vector machine (SVM) kernel function parameter optimization, finally get a more accurate classification of classifier
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
psoSVM
- 利用粒子群优化算法优化支持向量机的惩罚参数Cg，提高效率、准确率。-Particle swarm optimization algorithm to optimize SVM penalty parameter Cg, improve efficiency and accuracy.
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