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

DML discrete outcome #881

Open
nicolavizioli opened this issue May 3, 2024 · 1 comment
Open

DML discrete outcome #881

nicolavizioli opened this issue May 3, 2024 · 1 comment

Comments

@nicolavizioli
Copy link

Hi,
I saw that now DML (I'm using Linear) gives the possibility to select "discrete outcome=True", this means than now residuals of outcome model are not more only {-1,0,1} and then I can use a classifier like XGBClassifier() for outcome model?
thanks

@kbattocchi
Copy link
Collaborator

That's correct - if you set discrete_outcome=True then your y_model should be an sklearn classifier rather than a regressor and we'll use predict_proba rather than predict, so the residuals can take on any values in the range [-1,1].

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants