Semi-supervised Learning

Ways of Doing Semi-supervised algorithm

1. Transductive SVM ( minimize the risk directly )
   
2. Co-training and Tri-training ( using two/three different view of the same datasets)
   
3. Genetic Algorithm
   
4. Non-parametric approach ( modified KDE convergence algorithm )
   
5. Parametric approach ( modified EM algorithm )
6. Graph-based approach