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[ENH] interface to cyclic boosting package #132

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fkiraly opened this issue Oct 23, 2023 · 1 comment
Closed

[ENH] interface to cyclic boosting package #132

fkiraly opened this issue Oct 23, 2023 · 1 comment
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feature request New feature or request good first issue Good for newcomers interfacing algorithms Interfacing existing algorithms/estimators from third party packages module:regression probabilistic regression module

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@fkiraly
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fkiraly commented Oct 23, 2023

It would be nice to interface cyclic_boosting, which provides implementations of the cyclic boosting regressors.
Blue-Yonder-OSS/cyclic-boosting#56

They are popular in proba forecasting, but by nature are actually proba supervised regerssion algoritihms so "belong" in skpro, from where it can be interfaced by sktime for forecasting.

The interface to implement is in this extension template:
https://github.com/sktime/skpro/blob/main/extension_templates/regression.py

FYI @rijkvandermeulen, @FelixWick

@fkiraly fkiraly added good first issue Good for newcomers module:regression probabilistic regression module interfacing algorithms Interfacing existing algorithms/estimators from third party packages feature request New feature or request labels Oct 23, 2023
setoguchi-naoki added a commit to setoguchi-naoki/skpro that referenced this issue Jan 15, 2024
fkiraly pushed a commit that referenced this issue Jan 26, 2024
Implements #132 

① The interface for [Cyclic
boosting](https://github.com/Blue-Yonder-OSS/cyclic-boosting)
J-qpd estimation by quantile regression with Cyclic boosting, Output
distribution's parameters are given by j-qpd's loc and scale

② New distribution class, Johnson quantile parameterized-distribution

#### Does your contribution introduce a new dependency? If yes, which
one?
cyclic_boosting package>=1.2.1
@fkiraly
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fkiraly commented Jan 28, 2024

added with #144

@fkiraly fkiraly closed this as completed Jan 28, 2024
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Labels
feature request New feature or request good first issue Good for newcomers interfacing algorithms Interfacing existing algorithms/estimators from third party packages module:regression probabilistic regression module
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