Semi-Supervised/All Semi Supervised at main · ai-se/Semi-Supervised · GitHub

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## Inductive methods:

### Wrapper methods (Multiple supervised methods in each)
1. **Self-training (Done)**
  1. **Co-training (Done)**
  1. **Multi-view co-training (Done)**
  2. **CO-Forest (Done)**
  3. **Single-view co-training (Done)**
  4. Co-regularization
1. Boosting
  1. SSMBoost
  1. ASSEMBLE
  1. **SemiBoost (Done)**

### Unsupervised preprocessing
1. Feature extraction
2. **Cluster-then-label (Done)**
3. Pre-training

### Intrinsically semi-supervised methods
1. Maximum-margin methods
  1. **safe semi supervised Support vector machines(S4VM) (Done)**
  2. **Gaussian processes (working on now)**
  3. Density regularization
  4. **Pseudo-labelling as a form of margin maximization (working on now)**
2. Perturbation-based methods
  1. Pseudo-ensembles
  2. pi-model
  3. Temporal ensembling
  4. Mean teacher
  5. Semi-supervised mixup
### Others
  1. **LabelPropagation (Done)**
  2. **LabelSpreading (Done)**
  3. **Semi GMM (Done)**
  4. **EATT (Done)**
  5. **FTcF.MDS (Done)**
  6. **S3VM (Done)**