文件名称:Ensemble

  • 所属分类:
  • matlab例程
  • 资源属性:
  • [Matlab] [源码]
  • 上传时间:
  • 2012-11-26
  • 文件大小:
  • 1.57mb
  • 下载次数:
  • 0次
  • 提 供 者:
  • 李*
  • 相关连接:
  • 下载说明:
  • 别用迅雷下载,失败请重下,重下不扣分!

介绍说明--下载内容均来自于网络,请自行研究使用

用adaboost算法生成基支持向量机分类器,并对识别结果进行简单投票法集成。附有支持向量机工具箱和adaboost算法流程说明。-Adaboost algorithm to generate the base with a support vector machine classifier, and the recognition result is a simple voting method integration. With support vector machine algorithm toolbox and adaboost process descr iption.
相关搜索: ensemble
分类器
matlab

(系统自动生成,下载前可以参看下载内容)

下载文件列表

Ensemble\my_Adaboost\Adatest.m

........\...........\basic_SVM.asv

........\...........\basic_SVM.m

........\...........\cal_c_w.asv

........\...........\cal_c_w.m

........\...........\cal_distr.asv

........\...........\cal_distr.m

........\...........\cal_fin_e.asv

........\...........\cal_fin_e.m

........\...........\cal_t_er.asv

........\...........\cal_t_er.m

........\...........\fin_rule.asv

........\...........\fin_rule.m

........\...........\get_tr.asv

........\...........\get_tr.m

........\...........\init.asv

........\...........\init.m

........\...........\my_Ada.asv

........\...........\my_AdaFS.asv

........\...........\my_AdaM1.asv

........\...........\my_AdaM1.m

........\...........\set_weight.m

........\...........\st_data.asv

........\...........\st_data.m

........\...........\tr_weak.asv

........\...........\tr_weak.m

........\...........\upd_weight.asv

........\...........\upd_weight.m

........\...........\程序流程.xls

........\osu_svm3.00\cmap.mat

........\...........\Contents.m

........\...........\demo\c_clademo.m

........\...........\....\c_lindemo.m

........\...........\....\c_poldemo.m

........\...........\....\c_rbfdemo.m

........\...........\....\c_svcdemo.m

........\...........\....\DemoData_class.mat

........\...........\....\DemoData_test.mat

........\...........\....\DemoData_train.mat

........\...........\....\one_rbfdemo.m

........\...........\....\osusvmdemo.m

........\...........\....\SVMClassifier.mat

........\...........\....\u_clademo.m

........\...........\....\u_lindemo.m

........\...........\....\u_poldemo.m

........\...........\....\u_rbfdemo.m

........\...........\....\u_svcdemo.m

........\...........\demos.m

........\...........\LinearSVC.m

........\...........\mexSVMClass.dll

........\...........\mexSVMClass.m

........\...........\mexSVMClass.mexglx

........\...........\mexSVMClass.mexhp7

........\...........\mexSVMClass.mexsol

........\...........\mexSVMTrain.dll

........\...........\mexSVMTrain.m

........\...........\mexSVMTrain.mexglx

........\...........\mexSVMTrain.mexhp7

........\...........\mexSVMTrain.mexsol

........\...........\Normalize.m

........\...........\one_RbfSVC.m

........\...........\.su_svm200\clademo.m

........\...........\..........\Contents.m

........\...........\..........\c_svcdemo.m

........\...........\..........\DemoData_class.mat

........\...........\..........\DemoData_test.mat

........\...........\..........\DemoData_train.mat

........\...........\..........\demos.m

........\...........\..........\DimFit.m

........\...........\..........\lindemo.m

........\...........\..........\LinearSVC.m

........\...........\..........\mexSVMClass.dll

........\...........\..........\mexSVMClass.m

........\...........\..........\mexSVMTrain.dll

........\...........\..........\mexSVMTrain.m

........\...........\..........\mexSVMTrain_0.dll

........\...........\..........\mexSVMTrain_1.dll

........\...........\..........\mexSVMTrain_2.dll

........\...........\..........\one_rbfdemo.m

........\...........\..........\one_RbfSVC.m

........\...........\..........\osuSVMClass.m

........\...........\..........\osusvmdemo.m

........\...........\..........\osuSVMTest.m

........\...........\..........\osuSVMTrain.m

........\...........\..........\poldemo.m

........\...........\..........\PolySVC.m

........\...........\..........\rbfdemo.m

........\...........\..........\RbfSVC.m

........\...........\..........\svcdemo.m

........\...........\..........\SVMClass.m

........\...........\..........\SVMClassifier.mat

........\...........\..........\SVMTest.m

........\...........\..........\SVMTrain.m

........\...........\..........\u_clademo.m

........\...........\..........\u_lindemo.m

........\...........\..........\u_LinearSVC.m

........\...........\..........\u_poldemo.m

........\...........\..........\u_PolySVC.m

........\...........\..........\u_rbfdemo.m

........\...........\..........\u_RbfSVC.m

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