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

Always use partition based categorical splits. #7857

Merged
merged 4 commits into from May 3, 2022

Conversation

trivialfis
Copy link
Member

My mistake, we are always using regression trees.

@@ -83,7 +83,7 @@ inline void InvalidCategory() {
* \brief Whether should we use onehot encoding for categorical data.
*/
XGBOOST_DEVICE inline bool UseOneHot(uint32_t n_cats, uint32_t max_cat_to_onehot, ObjInfo task) {
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Remove task argument. I think with this change task can be removed from a lot of function arguments.

Copy link
Member Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Thank you for reminding me of that. All removed.

@trivialfis trivialfis merged commit 317d7be into dmlc:master May 3, 2022
@trivialfis trivialfis deleted the fix-cat-split branch May 3, 2022 14:30
trivialfis added a commit to trivialfis/xgboost that referenced this pull request May 6, 2022
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
Projects
None yet
Development

Successfully merging this pull request may close these issues.

None yet

2 participants