The Treebagger give different results in 2012a and 2013a
1 Ansicht (letzte 30 Tage)
Ältere Kommentare anzeigen
I used
B = TreeBagger(NTrees(j),train_feats',train_labels');
and
Y = predict(B,test_feats');
to classification, in train_feats each column is a sample,the train_labels total of 30 categories,label from 0 to 29.
when I run the code in matlab 2012a the accuracy almost 90%,but when i update to 2013a the accuracy is less than 1%. The data and the code are intact, why the result is so different?
Does anyone have an explanation?
0 Kommentare
Akzeptierte Antwort
Tom Lane
am 23 Apr. 2013
This might be the explanation, and it includes a suggestion of how to avoid the problem:
http://www.mathworks.com/support/bugreports/927692
Weitere Antworten (0)
Siehe auch
Kategorien
Mehr zu Classification Ensembles finden Sie in Help Center und File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!