Maximising entropy on the nonparametric predictive inference model for multinomial data

@article{Abelln2011MaximisingEO,
  title={Maximising entropy on the nonparametric predictive inference model for multinomial data},
  author={Joaqu{\'i}n Abell{\'a}n and Rebecca M. Baker and Frank P. A. Coolen},
  journal={European Journal of Operational Research},
  year={2011},
  volume={212},
  pages={112-122}
}
The combination of mathematical models and uncertainty measures can be applied in the area of data mining for diverse objectives with as final aim to support decision making. The maximum entropy function is an excellent measure of uncertainty when the information is represented by a mathematical model based on imprecise probabilities. In this paper, we present algorithms to obtain the maximum entropy value when the information available is represented by a new model based on imprecise… CONTINUE READING
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