xgboostby base learner
cvmethod also returns the prediction
multilabel_evaluationto also return the label measures
brplusbecause the newfeatures were using different levels
baselineusing hamming-loss to prevent empty label prediction
homerto deal with labels without intances and to predict instances based on the meta-label scores
New multi-label transformation methods including pairwise and multiclass approaches. Some fixes from previous version.
multilabel_confusion_matrixaccepts a data.frame or matrix with the predicitons
First release of utiml:
Binary Relevance (BR);
ConTRolled Label correlation exploitation (CTRL);
Dependent Binary Relevance (DBR);
Ensemble of Binary Relevance (EBR);
Ensemble of Classifier Chains (ECC);
Meta-Binary Relevance (MBR or 2BR);
Nested Stacking (NS);
Pruned and Confident Stacking Approach (Prudent); and,
Recursive Dependent Binary Relevance (RDBR)
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.