mex/standalone 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
Added Binaries for Windows 32/64 bit
Commented out compile_windows.m, if you feel upto it, remove the comments and recompile
CLASSIFICATION BASED RANDOMFOREST
****A tutorial for matlab now in tutorial_ClassRF.m****
Ways to generate Mex's and Standalone files
rfsub.o is compiled using fortran from rfsub.f. In case cywin or a fortran
compiler is not present just copy the appropriate (depending on OS)
rfsub.o from precompiled_rfsub directory to the current directory
___STANDALONE____ (not exactly standalone but an interface via C)
An example for a C file using the twonorm dataset for classification
is shown in src/twonorm_C_wrapper.cpp
This is a standalone version that needs to set right parameters in CPP file.
Compiling in windows:
Method 1: use cygwin and make: go to current directory and run 'make twonorm -f Makefile.windows'
in cygwin command prompt. Need to have gcc/g++ and g77 (in cygwin)
installed. Also the custom makefile differs from the linux version which has -lgfortran
whereas the windows version doesn't. Will generate twonorm_test.exe
Method 2: use DevC++ (download from http://www.bloodshed.net/devcpp.html ).
Open the twonorm_C_devc.dev file which is a project file which has the sources
etc set. Just compile and run. Will generate twonorm_C_devcpp.exe
Compiling in linux:
Method 1: use linux and make: go to this directory and run 'make diabetes'
in command prompt. Need to have gcc/g++ and fortran installed. Will generate diabetes_test.
run as ./diabetes_test
___MATLAB___
generates Mex files that can be called in Matlab directly.
Compiling in windows:
Use the compile_windows.m and run in windows. It will compile and generate
appropriate mex files. Need Visual C++ or some other compiler
(VC++ express edition also works). Won't work with Matlab's inbuilt compiler (lcc)
Compiling in linux:
Use the compile_linux.m and run in windows. It will compile and generate
appropriate mex files.
Using the Mex interface:
There are 2 functions classRF_train and classRF_predict as given below.
See the sample file test_ClassRF_extensively.m
%function Y_hat = classRF_predict(X,model)
%requires 2 arguments
%X: data matrix
%model: generated via classRF_train function
%function model = classRF_train(X,Y,ntree,mtry, extra_options)
%requires 2 arguments and the rest 2 are optional
%X: data matrix
%Y: target values
%ntree (optional): number of trees (default is 500)
%mtry (default is max(floor(D/3),1) D=number of features in X)
%there are about 14 odd options for extra_options. Refer to tutorial_ClassRF.m to examine them
Version History:
v0.02 (May-15-09):Updated so that classification package now has about 95% of the total options
that the R-package gives. Woohoo. Tracing of what happening behind screen works better.
v0.01 (Mar-22-09): very basic interface for mex/standalone to Liaw et al's
randomForest Package supports only ntree and mtry changing for time being.
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基于MATLAB实现的对图像特征的分类,随机森林算法是一类很好的算法+使用说明文档.rar
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CSDN IT狂飙上传的代码均可运行,功能ok的情况下才上传的,直接替换数据即可使用,小白也能轻松上手 【资源说明】 基于MATLAB实现的对图像特征的分类,随机森林算法是一类很好的算法+使用说明文档.rar 1、代码压缩包内容 主函数:main.m; 调用函数:其他m文件;无需运行 运行结果效果图; 2、代码运行版本 Matlab 2020b;若运行有误,根据提示GPT修改;若不会,私信博主(问题描述要详细); 3、运行操作步骤 步骤一:将所有文件放到Matlab的当前文件夹中; 步骤二:双击打开main.m文件; 步骤三:点击运行,等程序运行完得到结果; 4、仿真咨询 如需其他服务,可后台私信博主; 4.1 期刊或参考文献复现 4.2 Matlab程序定制 4.3 科研合作 功率谱估计: 故障诊断分析: 雷达通信:雷达LFM、MIMO、成像、定位、干扰、检测、信号分析、脉冲压缩 滤波估计:SOC估计 目标定位:WSN定位、滤波跟踪、目标定位 生物电信号:肌电信号EMG、脑电信号EEG、心电信号ECG 通信系统:DOA估计、编码译码、变分模态分解、管道泄漏、滤波器、数字信号处理+传输+分析+去噪、数字信号调制、误码率、信号估计、DTMF、信号检测识别融合、LEACH协议、信号检测、水声通信 5、欢迎下载,沟通交流,互相学习,共同进步!
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