RFR

  好用的随机森林回归（RFR），也可用与分类。基于以编译的mex84，可实现bias-correction。回归预测精度较高(applicable random forrest regression，can also be used for classification。Regress with bias-correction 。can achieve high accuracy)

Compile_Check_kcachegrind,611,2009-04-25
Compile_Check_memcheck,623,2009-04-25
compile_linux.m,952,2009-05-17
compile_windows.m,915,2010-02-06
diabetes_C_devc.dev,1293,2009-04-25
Makefile,1774,2009-05-17
mexRF_predict.mexw32,10752,2010-02-06
mexRF_predict.mexw64,11264,2010-02-06
mexRF_train.mexw32,25600,2010-02-06
mexRF_train.mexw64,34304,2010-02-06
README.txt,2750,2010-02-06
regRF_predict.m,986,2009-05-17
regRF_train.m,12930,2016-03-21
src
...\cokus.cpp,7678,2009-04-25
...\cokus_test.cpp,1189,2009-04-25
...\diabetes_C_wrapper.cpp,11673,2009-05-17
...\mex_regressionRF_predict.cpp,3864,2009-05-17
...\mex_regressionRF_train.cpp,12391,2009-05-17
...\qsort.c,4676,2009-04-25
...\reg_RF.cpp,40291,2009-05-17
...\reg_RF.h,560,2009-05-17
tempbuild
test_RegRF_extensively.m,1364,2009-05-17
tutorial_RegRF.m,9505,2009-05-17
Version_History.txt,384,2010-02-06
说明.txt,26,2016-01-25