fitcensemble settings to speed the process up
2 views (last 30 days)
Show older comments
Stephen Gray
on 12 Jan 2021
Commented: Stephen Gray
on 3 Feb 2021
I have a table with 260000 records, 9 fields of which 3 are categorical, the rest are double with the ninth being the target (0 or 1). I'm running fitcensemble as below :-
Mdl = fitcensemble(TestGB(:,1:8),TestGB(:,9),'OptimizeHyperparameters',...
'HyperparameterOptimizationOptions',struct('AcquisitionFunctionName','expected-improvement-plus'))
I've tried with less fields(3-4) and it runs reasonably quickly. With nine fields however it took overnight to do one round of calculations with 29 to go. As my machine only has 4 cores I thought I'd run it on an Amazon AWS compute VM with 16 Xeon processors only it didn't seem much quicker. Is there anything I'm doing wrong or that I could do to speed things up? Or am I just going to have to wait!
Stephen Gray
0 Comments
Accepted Answer
Aditya Patil
on 3 Feb 2021
You can use the
struct('UseParallel',true)
name-value pair to improve performance of the hyperparameter optimization. This requires parallel computing toolbox.
More Answers (0)
See Also
Categories
Find more on Classification Ensembles in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!