Propositionalisation of Multi-instance Data Using Random Forests

  title={Propositionalisation of Multi-instance Data Using Random Forests},
  author={Eibe Frank and Bernhard Pfahringer},
  booktitle={Australasian Conference on Artificial Intelligence},
Multi-instance learning is a generalisation of attribute-value learning where examples for learning consist of labeled bags (i.e. multisets) of instances. This learning setting is more computationally challenging than attribute-value learning and a natural fit for important application areas of machine learning such as classification of molecules and image classification. One approach to solve multi-instance learning problems is to apply propositionalisation, where bags of data are converted… CONTINUE READING


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