How to define fitcensemble matlab function?
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I am using following matlab code with latest MATLAB R2024b software
initIdx = 1:incrementSize;
Xinit = trainFeatures(initIdx,:);
Yinit = trainLabels(initIdx);
disp(size(Xinit));
disp(size(Yinit));
% Train initial batch model using fitcensemble
t = templateTree('MaxNumSplits',20); % You can adjust as needed
Mdl = fitcensemble(Xinit, Yinit, ...
'Method', 'Bag', ...
'NumLearningCycles', 100, ...
'Learners', t, ...
'OOBPrediction', 'on');
% Convert to incremental model
IncMdl = incrementalLearner(Mdl);
it is displaying [the following] error
3048 2
3048 1
Error using classreg.learning.FitTemplate/fillIfNeeded (line 734)
OOBPrediction is not a valid parameter name.
Error in classreg.learning.FitTemplate.make (line 140)
temp = fillIfNeeded(temp,type);
^^^^^^^^^^^^^^^^^^^^^^^
Error in fitensemble (line 363)
temp = classreg.learning.FitTemplate.make(method,'nlearn',nlearn,'learners',learners,varargin{:});
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Error in fitcensemble (line 215)
this = fitensemble(X, Y, Method, NumLearningCycles, Learners, ...
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Mdl = fitcensemble(Xinit, Yinit, ...
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
I request you to please suggest me how to resolve this issue.
댓글 수: 10
Walter Roberson
2024년 12월 19일
TreeBagger() as a function returns a TreeBagger object https://www.mathworks.com/help/stats/treebagger.html
There are no functions to convert TreeBagger objects to incremental learning objects.
The documentation at https://www.mathworks.com/help/stats/incremental-learning-overview.html#mw_b9f908d5-71f7-419a-9f6c-386f264864b9 describes the objects that can be converted to incremental learning.
- ClassificationECOC and CompactClassificationECOC
- ClassificationKernel
- ClassificationSVM and CompactClassificationSVM
- ClassificationLinear
- ClassificationNaiveBayes
- RegressionKernel
- RegressionSVM and CompactRegressionSVM
- RegressionLinear
Notice that TreeBagger() and ClassificationBaggedEnsemble and ClassificationEnsemble and ClassificationPartitionedEnsemble are not on this list.
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