The Classifier Chain Generalized Maximum Entropy Model for Multi-label Choice Problems

@inproceedings{Leurcharusmee2015TheCC,
  title={The Classifier Chain Generalized Maximum Entropy Model for Multi-label Choice Problems},
  author={Supanika Leurcharusmee and Jirakom Sirisrisakulchai and Songsak Sriboonchitta and Thierry Denoeux},
  booktitle={Econometrics of Risk},
  year={2015}
}
Multi-label classification can be applied to study empirically discrete choice problems, in which each individual chooses more than one alternative. We applied the Classifier Chain (CC) method to transform the Generalized Maximum Entropy (GME) choice model from a single-label model to a multi-label model. The contribution of our CC-GME model lies in the advantages of both the GME and CC models. Specifically, the GME model can not only predict each individual’s choice, but also robustly estimate… 

Pension Choices of Senior Citizens in Thailand:A Multi-Label Classification with Generalized Maximum Entropy

TLDR
This study applied the Classifier Chain Generalized Maximum Entropy (CC-GME) method to examine individual characteristics of senior citizens with different choices of pension options in Thailand to study correlated pension choice determinants.

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