https://github.com/samsonq/snapboost
Heterogeneous Newton Boosting Machine using decision trees and kernel ridges as learners.
https://github.com/samsonq/snapboost
boosting gradient-boosting
Last synced: 6 months ago
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Heterogeneous Newton Boosting Machine using decision trees and kernel ridges as learners.
- Host: GitHub
- URL: https://github.com/samsonq/snapboost
- Owner: samsonq
- License: mit
- Created: 2021-06-18T09:08:02.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2021-11-06T18:57:59.000Z (over 4 years ago)
- Last Synced: 2025-11-27T12:25:00.319Z (7 months ago)
- Topics: boosting, gradient-boosting
- Language: Python
- Homepage:
- Size: 5.86 KB
- Stars: 5
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# snapboost
## Hetergeneous Newton Boosting Machine
- Instead of using only decision trees as learners like XGBoost and LightGBM, HNBM uses a combination of decision trees and ridge regressors to learn more complicated patterns in data.
## Usage Instructions
* This project is published on [PyPI](https://pypi.org/project/snapboost/). To install package, run:
```
pip install snapboost
```