serengil / chefboost
A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4.5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting, Random Forest and Adaboost w/categorical features support for Python
Why this job: works in the areas we cover, but does not say which job it does
What it does
The easiest way to install ChefBoost framework is to download it from from PyPI. It's going to install the library itself and its prerequisites as well.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 6 months ago
- Stars
- 489
- +1 this week
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Python
- 100% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 98% closed
- 1 still open
- Pull requests
- 10 merged
- 0 waiting
- Releases
- None
- Never published
- No contributing guide
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- Python 100%
- Shell <1%
- Makefile <1%
Topics
- decision-trees
- gradient-boosting
- gradient-boosting-machine
- random-forest
- adaboost
- id3
- c45-trees
- cart
- regression-tree
- gbm
- data-mining
- gradient-boosting-machines
Project record
- JobOther AI tools
- StatusListed
- Commits409
- Forks101
- Watching15
- Stars in 28 days+1
- CreatedMar 6, 2019
- First seen by usNov 7, 2026
- CheckedNov 8, 2026