搜索资源列表
svm_v0.55beta.tar
- 支持向量机,matlab程序,很有用的,欢迎大家下载测试! -,matlab,,!
svm_v0.01beta.tar
- New in this version: Support for multi-class pattern recognition using maxwins, pairwise [4] and DAG-SVM [5] algorithms. A model selection criterion (the xi-alpha bound [6,7] on the leave-one-out cross-validation e
svm_v0.54beta.tar
- SVM 程序 用于模式识别 小样本学习 -SVM pattern recognition procedures for the small sample study
svm_v0.51beta.tar
- SVM源程序小样本分析 模式识别 用于SVM的初学者。 -SVM source of small samples for analysis SVM pattern recognition for beginners.
svm_v0.55beta
- 支持向量机学习中用到的Matlab编写的工具箱。-support vector machines used in the study prepared by the Matlab toolbox.
svm_v0[1].55beta.tar
- 用于进行所谓的支持向量机的分析，关键是对信号进行分类，用于处理非线性非平稳信号-used for the so-called support vector machines, the key is the signal classification for handling nonlinear non-stationary signals
svm_v0.55
- 支持向量机的MATLAB工具箱-SVM MATLAB Toolbox
svm_v0.55beta
- 支持向量积SVM的工具箱，Matlab板的。
svm_v0.55beta
- 支持向量机,可以在MATLAB环境下运行.
svm_v0.55beta
- 最新的支持向量机工具箱，有了它会很方便 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] V.N. Vapnik, \"The Nature of Statistical Le
svm_v0.55
- 支持向量机的MATLAB工具箱-SVM MATLAB Toolbox
svm_v0.55beta
- 最新的支持向量机工具箱，有了它会很方便 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] V.N. Vapnik, "The Nature of Statistical Lea
svm_v0.55beta.tar
- 支持向量机,matlab程序,很有用的,欢迎大家下载测试! -,matlab,,!
svm_v0.01beta.tar
- New in this version: Support for multi-class pattern recognition using maxwins, pairwise [4] and DAG-SVM [5] algorithms. A model selection criterion (the xi-alpha bound [6,7] on the leave-one-out cross-validation e
svm_v0.54beta.tar
- SVM 程序 用于模式识别 小样本学习 -SVM pattern recognition procedures for the small sample study
svm_v0.51beta.tar
- SVM源程序小样本分析 模式识别 用于SVM的初学者。 -SVM source of small samples for analysis SVM pattern recognition for beginners.
svm_v0[1].55beta.tar
- 用于进行所谓的支持向量机的分析，关键是对信号进行分类，用于处理非线性非平稳信号-used for the so-called support vector machines, the key is the signal classification for handling nonlinear non-stationary signals
svm_v0.55beta
- 支持向量积SVM的工具箱，Matlab板的。-SVM Support Vector plot of the toolbox, Matlab board.
svm_v0.54
- svm的分类和应用~~有详细的例子,非常实际和好用-svm classification and application ~ ~ There are detailed examples, very practical and easy to use ~ ~
svm_v0.55
- 支持向量机分类，可用于人工智能，模式识别，数据挖掘，时间序列预测-Data aggregation processing