Traditionally, in statistics, it was implicitly assumed that models which are the best predictors also have the best explanatory power. Lately, many examples have been provided that show that the best predictive models are often different from the best explanatory models. In this paper, we provide a theoretical explanation for this difference.
CITATION STYLE
Sriboonchitta, S., Longpré, L., Kreinovich, V., & Dumrongpokaphan, T. (2018). Why the best predictive models are often different from the best explanatory models: A theoretical explanation. In Studies in Computational Intelligence (Vol. 808, pp. 163–171). Springer Verlag. https://doi.org/10.1007/978-3-030-04263-9_12
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