gamlr | Gamma lasso regression | Machine Learning library

by TaddyLab C Version: Current License: No License

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kandi X-RAY | gamlr Summary

gamlr is a C library typically used in Artificial Intelligence, Machine Learning applications. gamlr has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

The Gamma Lasso ==. This package implements the gamma lasso algorithm for regularization paths corresponding to a range of non-convex cost functions between L0 and L1 norms. As much as possible, usage is analogous to that for the glmnet package (which does the same thing for penalization between L1 and L2 norms). The CRAN page is at If you use gamlr, please cite Taddy (2017), One-step estimator paths for concave regularization, Journal of Computational and Graphical Statistics.

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gamlr has a low active ecosystem.

It has 21 star(s) with 8 fork(s). There are 10 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 13 have been closed. On average issues are closed in 129 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of gamlr is current.

Quality

gamlr has no bugs reported.

Security

gamlr has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

gamlr does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

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gamlr releases are not available. You will need to build from source code and install.

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gamlr Key Features

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gamlr Examples and Code Snippets

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Community Discussions

Trending Discussions on gamlr

How to get the coefficents of a Cross Validated Lasso for a specific lambda (Not the “1se” or “min” lambda)

How do I use 'texir' and 'dmr' parameters?

QUESTION

How to get the coefficents of a Cross Validated Lasso for a specific lambda (Not the “1se” or “min” lambda)

Asked 2021-Mar-20 at 10:24

I run a CV Lasso with the cv.gamlr function in R. I can get the coefficients for the lambdas that correspond to the “1se” or “min” criterion.

...

ANSWER

Answered 2021-Mar-20 at 10:24

The coefficients are stored under lasso$gamlr$beta, in your example, you can access them like this:

Source https://stackoverflow.com/questions/66718416

QUESTION

How do I use 'texir' and 'dmr' parameters?

Asked 2018-Oct-03 at 09:27

I am trying to run a multinomial inverse regression as described here. The R package is called textir. It works just fine, but I am unable to map the parameters in the R package (called "nlambda" and "gamma") to (what I understand) are hyper parameters of the model as described in the paper (shape and scale parameters r and s of the gamma-hyperprior for each lambda).

...

ANSWER

Answered 2018-Oct-03 at 09:27

I actually missed the important part of the READ me:

"Versions 2+ make [..] differ from [...] original MNIR: penalties are chosen from full regularization paths (instead of being fixed)...". In case anyone else runs in the same problem, one can download version 1.8.8 from github and manually install. It will them work just fine.

Source https://stackoverflow.com/questions/52578869

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