How to get the prediction result of each decision tree in random forest?
5 views (last 30 days)
Show older comments
First I built a random forest regression model
RFModel6=TreeBagger(nTree,TrainVARI,TrainYield,...
'Method','regression','OOBPredictorImportance','on', 'MinLeafSize',nLeaf);
Then how can I get the predicted value of each decision tree?
0 Comments
Answers (1)
Ramtej
on 31 Aug 2023
Hi hanwen,
I understand that you are trying to predict value of each decision tree from the ensemble of bagged decision trees.
You can access an individual tree by using the "Trees" property of "TreeBagger" class and predict using each individual tree.
% Example
total_trees = RFModel6.Trees % cell array of trees
predicted_data = cell(nTree, 1) % dummy output cell array
for tree=1:nTree
predicted_data{tree} = predict(total_trees{tree}, X_input);
end
Hope this helps!
0 Comments
See Also
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!