engression
0.1.6Engression Modelling
Overview
Fits engression models for nonlinear distributional regression. Predictors and targets can be univariate or multivariate. Functionality includes estimation of conditional mean, estimation of conditional quantiles, or sampling from the fitted distribution. Training is done full-batch on CPU (the python version offers GPU-accelerated stochastic gradient descent). Based on "Engression: Extrapolation through the lens of distributional regression" by Xinwei Shen and Nicolai Meinshausen (2024) in JRSSB. Also supports classification (experimental). doi:10.1093/jrsssb/qkae108.
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- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 0%
- Documented parameters
- 100%
- Return-value docs
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- References docs
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Package metadata
- First published
- 2023-07-06
- Total releases
- 5 / 3 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 8.5 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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