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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
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