Can I remove the intercept?

DreHar commented 5 years ago

Hi All,

I'm sorry if I am just being dull, but is it possible to remove the intercept in GLM/GLMCV? I believe it is supported in the R version of glmnet (https://cran.r-project.org/web/packages/glmnet/ChangeLog version 1.9-3).

Could I comment out the intercept/beta0 calculations in pyglment.py and just set beta0 to 0?

Thanks!

jasmainak commented 5 years ago

It's not supported at the moment but it would be a welcome addition. You'd need a fit_intercept parameter which is a boolean

DreHar commented 5 years ago

I have made an attempt to add in fit_intercept as a parameter and made a [WIP] PR - #310

Please let me know if there are any changes or adjustments. There are a few style points I wasn't sure about. I am not sure if it would be better to

pass fit_intercept everywhere as a parameter
change all methods to expect beta0 and beta and pass beta0 as 0 for the no intercept case everywhere
in gradL2Loss, whether it should be one fit intercept check at the bottom and then calc by type, or multiple fit intercepts inside the current if else. Currently I just compute grad0 and then don't use it

What I have tried to do is add the fit_intercept parameter to the GLM and GLMCV classes. Then within all methods the state of fitintercept is inferred. Then before finishing the GLM class will separate out the beta0 and beta_. I had a look at sklearn.linear_models and this appeared to be how they handled it.

DreHar commented 5 years ago

Sorry, I just realised I made a mistake and I do have some unit test failures. I will fix these up; any style or directional change still much appreciated

jasmainak commented 5 years ago

That seems looks fair and yeah, I would try to mimic sklearn as much as possible. Thanks a lot for the PR!

jasmainak commented 4 years ago

closed by #310

glm-tools / pyglmnet

Can I remove the intercept? #308