0 个投票

Hello,
I am using ranfom forest with greedy optimization and it goes very slow. I don´t want to use the bayesian optimization. I wonder if I can specify the range to check.
Thank you
s = RandStream('mlfg6331_64');
reset(s);
options = statset("UseParallel",true,"UseSubstreams",true,"Streams",s);
myopts = struct('Optimizer','gridsearch','AcquisitionFunctionName','expected-
improvement-plus', 'ShowPlots',false); %'UseParallel',true,
classificationML = fitcensemble(...
predictors, ...
response, ...
'Method', 'Bag', ...
'NumLearningCycles', 100, ...
'Learners', template, ...
'ClassNames', [1; 2],'OptimizeHyperparameters',
{'MaxNumSplits','MinLeafSize'},'HyperparameterOptimizationOptions',
myopts,'Options',options);

请先登录，再回答此问题。

 采纳的回答

Amal Raj
Amal Raj 2023-3-14

0 个投票

Hi,
s = RandStream('mlfg6331_64');
reset(s);
options = statset("UseParallel",true,"UseSubstreams",true,"Streams",s);
myopts = struct('Optimizer','gridsearch','AcquisitionFunctionName','expected-improvement-plus',...
'ShowPlots',false,...
'SearchRange',struct('MaxNumSplits',[1,10],'MinLeafSize',[1,5]));
classificationML = fitcensemble(...
predictors, ...
response, ...
'Method', 'Bag', ...
'NumLearningCycles', 100, ...
'Learners', template, ...
'ClassNames', [1; 2],...
'OptimizeHyperparameters',{'MaxNumSplits','MinLeafSize'},...
'HyperparameterOptimizationOptions',myopts,...
'Options',options);
The SearchRange field specifies a structure with fields for each hyperparameter you want to search. The values of these fields are two-element vectors indicating the minimum and maximum values to search. In this example, the search range for MaxNumSplits is from 1 to 10, and the search range for MinLeafSize is from 1 to 5.
By specifying the search range, you can limit the set of hyperparameters to be searched, which can speed up the optimization process. However, be aware that if the optimal hyperparameters lie outside the specified range, you may not find the best model.

更多回答（0 个）

类别

在 帮助中心 和 File Exchange 中查找有关 Model Building and Assessment 的更多信息

产品

版本

R2022a

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by