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Pyglmnet: Python implementation of elastic-net regularized generalized linear models

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 23 Feb 2020Publisher:Zenodo
Authors: Mainak Jas; Titipat Achakulvisut; Aid Idrizović; Daniel E. Acuna; Matthew Antalek; Vinicius Marques; Tommy Odland; +15 Authors
Code repository: https://github.com/glm-tools/pyglmnet/tree/1.1.1

doi: 10.5281/zenodo.3679515 , 10.5281/zenodo.594705 , 10.5281/zenodo.3686564

Pyglmnet: Python implementation of elastic-net regularized generalized linear models

Abstract

Graceful handling of small Hessian term in coordinate descent solver that led to exploding update term Ensure full compatibility of GLM class with scikit-learn

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Keywords

group-lasso, machine-learning, elastic-net, glm, lasso, Python

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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