文件名称:ensemb-learning

  • 所属分类:
  • matlab例程
  • 资源属性:
  • [Matlab] [源码]
  • 上传时间:
  • 2016-11-09
  • 文件大小:
  • 436kb
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  • 0次
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  • li***
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处理非平衡问题的集成方法,基于随机森林的集成学习-Ensemble learning method,which is based on the random forest classifier, to deal with data imbalance problem
(系统自动生成,下载前可以参看下载内容)

下载文件列表





randomforest-matlab

...................\RF_Class_C

...................\..........\classRF_predict.m

...................\..........\classRF_train.m

...................\..........\Compile_Check

...................\..........\compile_linux.m

...................\..........\compile_windows.m

...................\..........\data

...................\..........\....\twonorm.mat

...................\..........\....\X_twonorm.txt

...................\..........\....\Y_twonorm.txt

...................\..........\Makefile

...................\..........\Makefile.windows

...................\..........\mexClassRF_predict.mexw32

...................\..........\mexClassRF_predict.mexw64

...................\..........\mexClassRF_train.mexw32

...................\..........\mexClassRF_train.mexw64

...................\..........\precompiled_rfsub

...................\..........\.................\linux64

...................\..........\.................\win32

...................\..........\.................\.....\rfsub.o

...................\..........\.................\win64

...................\..........\.................\.....\rfsub.o

...................\..........\README.txt

...................\..........\rfsub.o

...................\..........\src

...................\..........\...\classRF.cpp

...................\..........\...\classTree.cpp

...................\..........\...\cokus.cpp

...................\..........\...\cokus_test.cpp

...................\..........\...\mex_ClassificationRF_predict.cpp

...................\..........\...\mex_ClassificationRF_train.cpp

...................\..........\...\qsort.c

...................\..........\...\rf.h

...................\..........\...\rfsub.f

...................\..........\...\rfutils.cpp

...................\..........\...\twonorm_C_wrapper.cpp

...................\..........\tempbuild

...................\..........\test_ClassRF_extensively.m

...................\..........\tutorial_ClassRF.m

...................\..........\twonorm_C_devcpp.dev

...................\..........\Version_History.txt

...................\RF_Reg_C

...................\........\Compile_Check_kcachegrind

...................\........\Compile_Check_memcheck

...................\........\compile_linux.m

...................\........\compile_windows.m

...................\........\data

...................\........\....\diabetes.mat

...................\........\....\X_diabetes.txt

...................\........\....\Y_diabetes.txt

...................\........\diabetes_C_devc.dev

...................\........\Makefile

...................\........\mexRF_predict.mexw32

...................\........\mexRF_predict.mexw64

...................\........\mexRF_train.mexw32

...................\........\mexRF_train.mexw64

...................\........\README.txt

...................\........\regRF_predict.m

...................\........\regRF_train.m

...................\........\src

...................\........\...\cokus.cpp

...................\........\...\cokus_test.cpp

...................\........\...\diabetes_C_wrapper.cpp

...................\........\...\mex_regressionRF_predict.cpp

...................\........\...\mex_regressionRF_train.cpp

...................\........\...\qsort.c

...................\........\...\reg_RF.cpp

...................\........\...\reg_RF.h

...................\........\tempbuild

...................\........\test_RegRF_extensively.m

...................\........\tutorial_RegRF.m

...................\........\Version_History.txt

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