Quantification de l’incertitude

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Uncertainty Quantification

It is important to build machine learning models that will yield unbiased estimates of uncertainties in calculated outcomes. Due to the inherent randomness in the dataset and model, evaluation parameters such as the R2 score are random variables, and thus it is important to estimate the degree of uncertainty in the model. For an example of uncertainty quantification, see this article: Random Error Quantification in Machine Learning.

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