Learning from Cluster Examples

@article{Kamishima2003LearningFC,
  title={Learning from Cluster Examples},
  author={Toshihiro Kamishima and Fumio Motoyoshi},
  journal={Machine Learning},
  year={2003},
  volume={53},
  pages={199-233}
}
Learning from cluster examples (LCE) is a hybrid task combining features of two common grouping tasks: learning from examples and clustering. In LCE, each training example is a partition of objects. The task is then to learn from a training set, a rule for partitioning unseen object sets. A general method for learning such partitioning rules is useful in any situation where explicit algorithms for deriving partitions are hard to formalize, while individual examples of correct partitions are… CONTINUE READING
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