文件名称:ensemb-learning
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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
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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