Class membership probability estimates are important for many applications of data mining in which classification outputs are combined with other sources of information for decisi...
Efficient estimation of tail probabilities involving heavy tailed random variables is amongst the most challenging problems in Monte-Carlo simulation. In the last few years, appli...
While deciphering the Enigma Code during World War II, I.J. Good and A.M. Turing considered the problem of estimating a probability distribution from a sample of data. They derive...
Accurate, well-calibrated estimates of class membership probabilities are needed in many supervised learning applications, in particular when a cost-sensitive decision must be mad...
The present article considers estimating a parameter θ in an imprecise probability model (Pθ)θ∈Θ which consists of coherent upper previsions Pθ . After the definition of a...