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Semi-Supervised Learning Methods

  • Many methods exist: EM with generative mixture models, self-training, co-training, data-based methods, transductive SVM, graph-based methods, …
  • Inductive methods and Transductive methods
    • Transductive methods: only label the available unlabeled data – not generating a classifier
    • Inductive methods: not only produce labels for unlabeled data, but also generate a classifier
  • Algorithmic methods
    • Classifier-based methods: start from an initial classifier, and iteratively enhance it
    • Data-based methods: find an inherent geometry in the data, and use the geometry to find a good classifier


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