wiki/forecasting/probablistic/level-set-forecaster/

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wiki/forecasting/probablistic/level-set-forecaster/

This note is a more detailed version of Algorithm 1 in:
Hasson H, Wang B, Januschowski T, Gasthaus J. Probabilistic forecasting: A level-set approach. Adv Neural Inf Process Syst. 2021;34: 6404–6416. Available: https://proceedings.neurips.cc/paper/2021/hash/32b127307a606effdcc8e51f60a45922-Abstract.html.
It maybe hard to comprehend without reading the texts before Algorithm 1.
A level set forecaster converts point forecaster to probabilistic forecasters by constructing the [[level set]] Level Set Level set can be used in ML of the forecaster1.
Given a point forecaster $f(x_1, \cdots, x_d)$ trained on dataset $\mathcal D = {(\mathcal x_i, y_i)}$, we collect the predictions and true values and build a map, $f(x_i) \to [y_{i_1}, y_{i_2}, \cdots, y_{i_m}]$.

https://datumorphism.leima.is/wiki/forecasting/probablistic/level-set-forecaster/