Description
Boosting methods can be readily extended to the semi-supervised setting, by introducing pseudo-labeled data after each learning step; which gives rise to the idea of semi-supervised boosting methods. The pseudo-labeling approach of self- training and co-training can be easily extended to boosting methods. Several boosting methods such as SSMBoost, ASSEMBLE, SemiBoost, RegBoost, etc can be found which can be applied for utilizing unlabeled datasets for supervised classifiers.
Technical Details
| Framework | MITRE D3FEND |
| Ontology URI | d3f:Semi-supervisedBoosting |
| Local Identifier | Semi-supervisedBoosting |
| Publication Status | Exists in ontology only |