-
Notifications
You must be signed in to change notification settings - Fork 540
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
FIL to import categorical models from treelite #4173
FIL to import categorical models from treelite #4173
Conversation
levsnv
commented
Aug 23, 2021
•
edited
Loading
edited
- importing forests with categorical nodes from Treelite
- python tests for lightgbm forests fit on categorical features and containing categorical nodes as well as numerical nodes in the same forest
- above tests include multiclass (GBDT) tests
- sklearn internally transforms categorical features into numerical: RandomForestClassifier GradientBoostingClassifier
- (cuml RF tests can come separately, if needed)
- (xgboost tests can come separately, if needed)
This reverts commit 472575d.
cpu inference supports categorical nodes data generation supports categorical features moved is_categoricals_h generation from GPU to CPU (value flow more obvious) fitted parameters to conventions neater memory management
…osed to forest construction one
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Approved, provided that the comments are addressed.
This reverts commit 8ccdb27.
Codecov Report
@@ Coverage Diff @@
## branch-21.10 #4173 +/- ##
===============================================
Coverage ? 86.07%
===============================================
Files ? 231
Lines ? 18652
Branches ? 0
===============================================
Hits ? 16055
Misses ? 2597
Partials ? 0
Flags with carried forward coverage won't be shown. Click here to find out more. Continue to review full report at Codecov.
|
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
LGTM! Great work!
rerun tests |
1 similar comment
rerun tests |
rerun tests
|
@gpucibot merge |
rerun tests |
@gpucibot merge |
1 similar comment
@gpucibot merge |
* importing forests with categorical nodes from Treelite * python tests for lightgbm forests fit on categorical features and containing categorical nodes as well as numerical nodes in the same forest * above tests include multiclass (GBDT) tests * sklearn internally transforms categorical features into numerical: [RandomForestClassifier](https://scikit-learn.org/0.24/modules/generated/sklearn.ensemble.RandomForestClassifier.html#sklearn.ensemble.RandomForestClassifier.fit) [GradientBoostingClassifier](https://scikit-learn.org/0.24/modules/generated/sklearn.ensemble.GradientBoostingClassifier.html#sklearn.ensemble.GradientBoostingClassifier.fit) * (cuml RF tests can come separately, if needed) * (xgboost tests can come separately, if needed) Authors: - Levs Dolgovs (https://github.com/levsnv) - Dante Gama Dessavre (https://github.com/dantegd) Approvers: - https://github.com/Salonijain27 - Andy Adinets (https://github.com/canonizer) - William Hicks (https://github.com/wphicks) - Dante Gama Dessavre (https://github.com/dantegd) URL: rapidsai#4173