fitcensemble settings to speed the process up
5 visualizaciones (últimos 30 días)
Mostrar comentarios más antiguos
Stephen Gray
el 12 de En. de 2021
Comentada: Stephen Gray
el 3 de Feb. de 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 comentarios
Respuesta aceptada
Aditya Patil
el 3 de Feb. de 2021
You can use the
struct('UseParallel',true)
name-value pair to improve performance of the hyperparameter optimization. This requires parallel computing toolbox.
Más respuestas (0)
Ver también
Categorías
Más información sobre Classification Ensembles en Help Center y File Exchange.
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!