How to get optimal tree when using random forest method

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Mekala balaji
Mekala balaji 2016 年 12 月 27 日
Hi,
I use the
meas=[...
[53.4
194.5
220.5
273.1
312.3
331.7
159.7
199.5
293.9
390.7
392.1
398.9
399.1
400.3
52.1
249.3
357.7
44.8
163.9
200.5
335.1
92.4
130.3
77.1]]
species=[{'v16'
'v6'
'v1'
'v126'
'v6'
'v1'
'v16'
'v6'
'v5'
'v156'
'v6'
'v1'
'v16'
'v6'
'v12456'
'v56'
'v256'
'v2456'
'v6'
'v16'
'v1234'
'v16'
'v12356'
'v6'}]
I use below code:
b = TreeBagger(50,meas,species,'oobpred','on')
But how to get optimal tree? Many thanks in advance.

回答 (2 件)

mizuki
mizuki 2016 年 12 月 30 日
Optimize tree with Bayesian Optimization (use bayesopt function). This feature is introduced in R2016b.
  • Tune Random Forest Using Quantile Error and Bayesian Optimization
Also you can search optimal parameters with other methods such as gridsearch, but you need to write code. For gridsearch, this might help you:
  • How to do grid Search to optimize sigma using Matlab?
  2 件のコメント
Amy Xu
Amy Xu 2017 年 4 月 19 日
I'm trying to run the following Mathworks example with my own X and Y:
"Tune Random Forest Using Quantile Error and Bayesian Optimization"
https://jp.mathworks.com/help/stats/tune-random-forest-using-quantile-error-and-bayesian-optimization.html
But, I'm getting the following error:
Undefined function or variable 'Y'.
I have attached the modified code (place both files in one folder on your PC drive). Can anyone help?
Marta Caneda Portela
Marta Caneda Portela 2022 年 9 月 6 日
What if I also need 5-fold cross-validation? I can't find any examples online

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Don Mathis
Don Mathis 2017 年 4 月 20 日
You could also try to find the best ensemble like this:
fitcensemble(meas,species,'OptimizeHyperparameters','all')
This will also try boosted decision trees in addition to random forests.

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