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Remove members of compact regression ensemble


cens1 = removeLearners(cens,idx)


cens1 = removeLearners(cens,idx) creates a compact regression ensemble identical to cens only without the ensemble members in the idx vector.

Argumentos de entrada


Compact regression ensemble, constructed with compact.


Vector of positive integers with entries from 1 to cens.NumTrained, where cens.NumTrained is the number of members in cens. cens1 contains the members of cens except those with indices in idx.

Typically, you set idx = j:cens.NumTrained for some positive integer j.

Output Arguments


Compact regression ensemble, identical to cens except cens1 does not contain members of cens with indices in idx.


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Create a compact regression ensemble. Compact it further by removing members of the ensemble.

Load the carsmall data set and select Weight and Cylinders as predictors.

load carsmall
X = [Weight Cylinders];

Train a regression ensemble using LSBoost. Specify tree stumps as the weak learners.

t = templateTree('MaxNumSplits',1);
ens = fitrensemble(X,MPG,'Method','LSBoost','Learners',t,...

Create a compact classification ensemble cens from ens.

cens = compact(ens);

Remove the last 50 members of the ensemble.

idx = cens.NumTrained-49:cens.NumTrained;
cens1 = removeLearners(cens,idx);


  • Typically, set cens1 equal to cens to retain just one ensemble.

  • Removing learners reduces the memory used by the ensemble and speeds up its predictions.

Consulte también