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- 535 creator joydeep-ghosh.
- 535 creator kunal-punera.
- 535 type InProceedings.
- 535 label "Enhanced Hierarchical Classification via Isotonic Smoothing".
- 535 sameAs 535.
- 535 abstract "Hierarchical topic taxonomies have proliferated on the World Wide Web~\cite{dmoz,yahoodir}, and exploiting the output space decompositions they induce in automated classification systems is an active area of research. In many domains, classifiers learned on a hierarchy of classes have been shown to outperform those learned on a flat set of classes. In this paper we argue that the hierarchical arrangement of classes leads to intuitive relationships between the corresponding classifiers' output scores, and that enforcing these relationships as a post-processing step to classification can improve its accuracy. We formulate the task of smoothing classifier outputs as a regularized isotonic tree regression problem, and present a dynamic programming based method that solves it optimally. This new problem generalizes the classic isotonic tree regression problem, and both, the new formulation and algorithm, might be of independent interest. In our empirical analysis of two real-world text classification scenarios, we show that our approach to smoothing classifier outputs results in improved classification accuracy.".
- 535 hasAuthorList authorList.
- 535 hasTopic World_Wide_Web.
- 535 isPartOf proceedings.
- 535 keyword "Dynamic Programming".
- 535 keyword "Hierarchical Classification".
- 535 keyword "Regularized Isotonic Regression".
- 535 keyword "Taxonomies".
- 535 title "Enhanced Hierarchical Classification via Isotonic Smoothing".