Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Reporting on tidymodels #122

Open
mbac opened this issue Jan 29, 2021 · 9 comments
Open

Reporting on tidymodels #122

mbac opened this issue Jan 29, 2021 · 9 comments
Labels
enhancement 💥 Implemented features can be improved or revised low priority 😴 This issue can be easily workaround or happens only in edge cases

Comments

@mbac
Copy link

mbac commented Jan 29, 2021

Question and context

Hi,

I've been using a tidymodels approach to perform a logistic regression. The glm model is stored in various objects, including the top-level workflow. This has some extractor functions which return a model (e.g.: pull_workflow_spec()), but report says it can't work with it. The workflow-model's class() is [_glm, model_fit].

Is there a way to use report directly on a tidymodels- (or parsnip-) generated model?

Thanks!

@strengejacke
Copy link
Member

Not sure how others see this, but for me personally the tidymodels framework is of rather low priority. Currently, there's no explicit support for tidymodels, however, this might change quite quickly.

@DominiqueMakowski
Copy link
Member

@mbac supporting tidymodels in report would require adding its support in the other easystats packages, i.e., insight, parameters, performance and effectsize, which is not the case currently.

That said, this is something we will probably want to add (as our goal is to have quite an extensive coverage of the R ecosystem) at some point, though I cannot give you any timeline ☺️ Stay tuned, though! I will open an issue on insight to track the progress as it would be the first step.

@IndrajeetPatil IndrajeetPatil added low priority 😴 This issue can be easily workaround or happens only in edge cases enhancement 💥 Implemented features can be improved or revised labels Feb 3, 2021
@strengejacke
Copy link
Member

tidymodels is now supported in insight, parameters and performance.

@mbac
Copy link
Author

mbac commented Mar 30, 2021

Thank you very much for taking care of this!

@strengejacke
Copy link
Member

@mattansb is it much effort to implement in effectsize?

@mattansb
Copy link
Member

No idea. Aren't most tidymodels' models non-parametric? (I have never used tidymodels before, only caret).

Anyway, if someone can open an issue over at effectsize with some examples, I can start working on these when I get beck next week (:

@strengejacke
Copy link
Member

strengejacke commented Mar 31, 2021

tidymodels returns an object of class model_fit, where object$fit is the actual model object. So you generally could do this:

foo.model_fit <- function(x, ...) {
  foo(x$fit, ...)
}

@strengejacke
Copy link
Member

tidymodels is just a more complicated way of fitting models in R. ;-)

@CWen001
Copy link

CWen001 commented Aug 23, 2022

It seems recently that tidymodels is almost mature, and its fitted model or workflow can provide a unified interface. Really looking forward to seeing report fully support tidymodels.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
enhancement 💥 Implemented features can be improved or revised low priority 😴 This issue can be easily workaround or happens only in edge cases
Projects
None yet
Development

No branches or pull requests

6 participants