• Corpus ID: 247315672

Accounting for uncertainty of non-linear regression models by divisive data resorting

  title={Accounting for uncertainty of non-linear regression models by divisive data resorting},
  author={Andrew Polar and Michael Poluektov},
This paper focuses on building models of stochastic systems with aleatoric uncertainty. The nature of the considered systems is such that the identical inputs can result in different outputs, i.e. the output is a random variable. This paper sug-gests a novel algorithm of boosted ensemble training of multiple models for obtaining a probability distribution of an individual output as a function of a system input. The deterministic component in the ensemble can be an arbitrarily-chosen regression… 

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