Sequence Learning from Data with Multiple Labels

@inproceedings{Dredze2009SequenceLF,
  title={Sequence Learning from Data with Multiple Labels},
  author={Mark Dredze and Partha Pratim Talukdar and Koby Crammer},
  year={2009}
}
Hierarchical multi-label classification (HMLC) is a variant of classification where instances may belong to multiple classes that are organized in a hierarchy. The approach we used is based on decision trees and is set in the predictive clustering trees framework (PCTs), which is implemented in the CLUS system. In this work, we are investigating how different distance measures for hierarchies influence the predictive performance of the PCTs. The distance measures that we consider include… CONTINUE READING
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