Remove members of compact classification ensemble
cens1 = removeLearners(cens,idx)
Compact classification ensemble, constructed with
Vector of positive integers with entries from
Typically, you set
Compact classification ensemble, identical to
Create a compact classification ensemble. Compact it further by removing members of the ensemble.
ionosphere data set.
Train a classification ensemble for the
ionosphere data using AdaBoostM1. Specify tree stumps as the weak learners.
t = templateTree('MaxNumSplits',1); ens = fitcensemble(X,Y,'Method','AdaBoostM1','Learners',t);
Create a compact classification ensemble
cens = compact(ens);
Remove the last 50 members of the ensemble.
idx = cens.NumTrained-49:cens.NumTrained; cens1 = removeLearners(cens,idx);
cens1 equal to
retain just one ensemble.
Removing learners reduces the memory used by the ensemble and speeds up its predictions.
This function fully supports GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).