资源简介
随机森林 想就拿去
代码片段和文件信息
%**************************************************************
%* mex interface to Andy Liaw et al.‘s C code (used in R package randomForest)
%* Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
%* License: GPLv2
%* Version: 0.02
%
% Calls Classification Random Forest
% A wrapper matlab file that calls the mex file
% This does prediction given the data and the model file
% Options depicted in predict function in http://cran.r-project.org/web/packages/randomForest/randomForest.pdf
%**************************************************************
%function [Y_hat votes] = classRF_predict(Xmodel extra_options)
% requires 2 arguments
% X: data matrix
% model: generated via classRF_train function
% extra_options.predict_all = predict_all if set will send all the prediction.
%
%
% Returns
% Y_hat - prediction for the data
% votes - unnormalized weights for the model
% prediction_per_tree - per tree prediction. the returned object .
% If predict.all=TRUE then the individual component of the returned object is a character
% matrix where each column contains the predicted class by a tree in the forest.
%
%
% Not yet implemented
% proximity
function [Y_new votes prediction_per_tree] = classRF_predict(Xmodel extra_options)
tic;
if nargin<2
error(‘need atleast 2 parametersX matrix and model‘);
end
if exist(‘extra_options‘‘var‘)
if isfield(extra_options‘predict_all‘)
predict_all = extra_options.predict_all;
end
end
if ~exist(‘predict_all‘‘var‘); predict_all=0;end
[Y_hatprediction_per_treevotes] = mexClassRF_predict(X‘model.nrnodesmodel.ntreemodel.xbestsplitmodel.classwtmodel.cutoffmodel.treemapmodel.nodestatusmodel.nodeclassmodel.bestvarmodel.ndbigtreemodel.nclass predict_all);
%keyboard
votes = votes‘;
clear mexClassRF_predict
Y_new = double(Y_hat);
new_labels = model.new_labels;
orig_labels = model.orig_labels;
for i=1:length(orig_labels)
Y_new(find(Y_hat==new_labels(i)))=Inf;
Y_new(isinf(Y_new))=orig_labels(i);
end
1;
t = toc;
disp([mfilename ‘总的运行时间为‘ num2str(t)])
属性 大小 日期 时间 名称
----------- --------- ---------- ----- ----
文件 202 2011-05-28 23:40 RF_Class_C\c.mat
文件 2228 2011-08-14 01:40 RF_Class_C\classRF_predict.m
文件 14987 2011-08-14 00:02 RF_Class_C\classRF_train.asv
文件 14895 2011-08-14 00:24 RF_Class_C\classRF_train.m
文件 856 2011-05-28 23:40 RF_Class_C\Compile_Check
文件 557 2011-05-28 23:40 RF_Class_C\compile_linux.m
文件 1720 2011-05-28 23:40 RF_Class_C\compile_windows.asv
文件 1740 2011-05-28 23:40 RF_Class_C\compile_windows.m
文件 48856 2011-05-28 23:40 RF_Class_C\data\twonorm.mat
文件 96300 2011-05-28 23:40 RF_Class_C\data\X_twonorm.txt
文件 600 2011-05-28 23:40 RF_Class_C\data\Y_twonorm.txt
文件 283471 2011-05-29 16:18 RF_Class_C\m.mat
文件 2693 2011-05-28 23:40 RF_Class_C\Makefile
文件 2523 2011-05-28 23:40 RF_Class_C\Makefile.windows
文件 20992 2011-05-28 23:40 RF_Class_C\mexClassRF_predict.mexw32
文件 26624 2011-05-28 23:40 RF_Class_C\mexClassRF_predict.mexw64
文件 32256 2011-05-28 23:40 RF_Class_C\mexClassRF_train.mexw32
文件 46080 2011-05-28 23:40 RF_Class_C\mexClassRF_train.mexw64
文件 6848 2011-05-28 23:40 RF_Class_C\precompiled_rfsub\win32\rfsub.o
文件 9840 2011-05-28 23:40 RF_Class_C\precompiled_rfsub\win64\rfsub.o
文件 3255 2011-05-28 23:40 RF_Class_C\README.txt
文件 9840 2011-05-28 23:40 RF_Class_C\rfsub.o
文件 33889 2011-05-28 23:40 RF_Class_C\src\classRF.cpp
文件 8947 2011-05-28 23:40 RF_Class_C\src\classTree.cpp
文件 7678 2011-05-28 23:40 RF_Class_C\src\cokus.cpp
文件 1189 2011-05-28 23:40 RF_Class_C\src\cokus_test.cpp
文件 5225 2011-05-28 23:40 RF_Class_C\src\mex_ClassificationRF_predict.cpp
文件 8545 2011-05-28 23:40 RF_Class_C\src\mex_ClassificationRF_train.cpp
文件 4676 2011-05-28 23:40 RF_Class_C\src\qsort.c
文件 5186 2011-05-28 23:40 RF_Class_C\src\rf.h
............此处省略21个文件信息
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