Effacer les filtres
Effacer les filtres

How to re-train a model optimized by Bayesian optimization on new data?

12 vues (au cours des 30 derniers jours)
Hi,
I optimized a regression ensemble
model = fitrensemble(X,Y,...);
with active HyperparameterOptimizationOptions, so the resulting model object of type RegressionBaggedEnsemble contains a HyperparameterOptimizationResults object. How can I use this easily to re-train the model on a new data set with the best point found by the hyperparameter optimization algorithm? Something like this would be nice:
newModel = fitrensemble(Xnew,YNew,model.HyperparameterOptimizationResults.bestPoint);
My current approach is tedious, because I have to distinguish between the method the optimization algorithm selected (Bag,LSBoost) and set all parameters manually (and I'm even not sure if this is correct):
best = model.HyperparameterOptimizationResults.bestPoint;
ttmp = templateTree('MinLeafSize',best.MinLeafSize,'MaxNumSplits',...
best.MaxNumSplits,'NumVariablesToSample',best.NumVariablesToSample);
if best.Method=='Bag' %#ok<BDSCA>
newModel = fitrensemble(Xnew,YNew,...
'Method','Bag','Learners',ttmp,'NumLearningCycles',best.NumLearningCycles);
else
newModel = fitrensemble(Xnew,YNew,...
'Method','LSBoost','Learners',ttmp,'NumLearningCycles',best.NumLearningCycles,'LearnRate',best.LearnRate);
end
This question is not restricted to fitrensemble, but includes all similar model functions available in Statistics and Machine Learning Toolbox (fitrlinear, fitrgp ...).

Réponse acceptée

Don Mathis
Don Mathis le 20 Sep 2019
Modifié(e) : Don Mathis le 20 Sep 2019
Your current approach (explicitly passing the values that the optimization found) is the right way to do it.
There is a faster/simpler way which uses undocumented functionality, and which therefore may change in the future. So, use at your own risk. You create a template from your model and then fit it:
model = fitrensemble(X,Y,...);
tmp = classreg.learning.FitTemplate.makeFromModelParams(model.ModelParameters);
newModel = fit(tmp,Xnew,Ynew)
  2 commentaires
Sinan Islam
Sinan Islam le 24 Avr 2021
Modifié(e) : Sinan Islam le 16 Juil 2021
@Don Mathisis this still the only way to retrain a model on new data (without using Classification Learner App)? Have MATLAB implemented a more formal method?
Denys Romanenko
Denys Romanenko le 1 Avr 2023
@Don Mathis and @Sebastian: Is there an analogue approach to retrain a fitcecoc - classifier? Unfortunately the above described approach is not applicable.
Thank you!

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