Learning from both experts and data

HIGHLIGHTS

• who: Firstname Lastname et al. from the XPop, Inria Saclay, Palaiseau, France have published the research work: Learning from Both Experts and Data, in the Journal: Entropy 2019, 21, 1208 of /2019/
• what: The authors show both empirically and theoretically that the proposed estimator is always more efficient than the best of the two models (expert or data) within a constant. The authors aim to estimate the distribution where D is the random variable disease. The authors aim to estimate the 2 J=K different combinations (as P[ B1,..., BL | D ], for example) when the . . .
  

   

  

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