machinelearnjs / machinelearnjs/machinelearnjs
feature/GradientBoostingClassifier and GradientBoostingRegressor
Nobody has claimed this yet.
- Dominant language
- TypeScript
- Stars
- 540
- Forks
- 53
- PR merge metrics
- No merged PRs in 30d
Description
-
I'm submitting a ...
[/] feature request -
Summary
Gradient Boosting is the most widely used model in Kaggle competitions for both classification and regression problems. It would be nice to introduce boosting algorithms to Kalimdor starting from the standard GradientBoostingClassifier and GradientBoostingRegressor. Benefits of taking this ticket:
- GB model is no longer a black box to you when you are using it
- Write declarative code that can be understood by anyone; great for spreading the knowledge
- Becoming part of the growing open source project
- Have fun
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue does not name any files, tests, or entry points. Start by surveying the existing machine-learning model APIs in the repository, then define the supported GradientBoostingClassifier and GradientBoostingRegressor behavior and tests before implementation; done means both models are integrated and their classification and regression behavior is covered.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- typescript
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100