Metadata-Version: 2.4
Name: snapboost
Version: 0.1.3
Summary: Heterogeneous Newton Boosting Machine
Home-page: https://github.com/samsonq/snapboost
Author: Samson Qian
Author-email: samsonqian@gmail.com
License: MIT
Keywords: boosting gradient-boosting snapboost
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas~=0.24.2
Requires-Dist: numpy~=1.18.1
Requires-Dist: scipy==1.2.1
Requires-Dist: matplotlib~=3.0.3
Requires-Dist: seaborn==0.9.0
Requires-Dist: scikit-learn~=0.23.2
Requires-Dist: future~=0.18.2
Requires-Dist: tqdm~=4.50.2
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# 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
  ```
