Supervised versus multiple instance learning: an empirical comparison

  title={Supervised versus multiple instance learning: an empirical comparison},
  author={Soumya Ray and Mark Craven},
We empirically study the relationship between supervised and multiple instance (MI) learning. Algorithms to learn various concepts have been adapted to the MI representation. However, it is also known that concepts that are PAC-learnable with one-sided noise can be learned from MI data. A relevant question then is: how well do supervised learners do on MI data? We attempt to answer this question by looking at a cross section of MI data sets from various domains coupled with a number of learning… CONTINUE READING
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