Cross-validation of single binary learners in multiclass classification (fitcecoc)
1 回表示 (過去 30 日間)
古いコメントを表示
I am training a multiclass classification model based on SVM using the function fitcecoc with coding design 'allpairs', meaning that binary models are trained for all possible combinations of class pairs.
You can cross-validate this multiclass (ECOC) classifier and estimate its generalization error by for example doing:
Mdl = fitcecoc(X,Y,'Learners',t,...
'ClassNames',{'setosa','versicolor','virginica'});
CVMdl = crossval(Mdl);
oosLoss = kfoldLoss(CVMdl)
In addition to this, would it also be possible to cross-validate and estimate the generalization error for the single binary models?
0 件のコメント
回答 (0 件)
参考
カテゴリ
Help Center および File Exchange で Classification についてさらに検索
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!