The goal of a machine learning regression problem is to predict a single numeric value. Quantile regression is a variation where you are concerned with under-prediction or over-prediction. I'll phrase ...
The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 49, No. 3 (September/septembre 2021), pp. 698-730 (33 pages) We propose a flexible Bayesian semiparametric quantile ...
By using a custom loss function that penalizes low predictions more than high predictions, you can coerce the network to make high predictions to a specified quantile value, such as 90th percentile.
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