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Aug 29, 2013 · Did you know that Decision Forests (or Random Forests, I think they are pretty much the same thing) are implemented in MATLAB? In MATLAB, Decision Forests go under the rather deceiving name of TreeBagger. Here’s a quick tutorial on how to do classification with the TreeBagger class in MATLAB. % Since TreeBagger uses randomness we … Continue reading "MATLAB – TreeBagger example"

Feb 27, 2014 · Random Forest for Matlab This toolbox was written for my own education and to give me a chance to explore the models a bit. It is NOT intended for any serious applications and it does not NOT do many of things you would want a mature implementation to do, like leaf pruning.

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Grows a quantile random forest of regression trees. Estimates conditional quartiles (Q 1, Q 2, and Q 3) and the interquartile range (I Q R) within the ranges of the predictor variables. Compares the observations to the fences, which are the quantities F 1 = Q 1-1. 5 I Q R and F 2 = Q 3 + 1. 5 I Q R. Any observation that is less than F 1 or ...

The study of forest fire prediction is of great environmental and scientific significance. China’s Guangxi Autonomous Region has a high incidence rate of forest fires. At present, there is little research on forest fires in this area. The application of the artificial neural network and support vector machines (SVM) in forest fire prediction in this area can provide data for forest fire ...

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/***** Copyright (C) 2001-7 Leo Breiman, Adele Cutler and Merck & Co., Inc. This program is free software; you can redistribute it and/or modify it under the terms of ...

Save the current state of the random number generator and create a 1-by-5 vector of random numbers. s = rng; r = rand(1,5) r = 1×5 0.8147 0.9058 0.1270 0.9134 0.6324