https://github.com/samuelmarks/ml-params-xgboost

XGBoost implementation of ml-params CLI API
https://github.com/samuelmarks/ml-params-xgboost

Last synced: 2 months ago
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XGBoost implementation of ml-params CLI API

• Host: GitHub
• URL: https://github.com/samuelmarks/ml-params-xgboost
• Owner: SamuelMarks
• License: apache-2.0
• Created: 2020-07-10T01:17:32.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2020-07-12T03:27:28.000Z (almost 6 years ago)
• Last Synced: 2025-03-23T01:28:01.085Z (over 1 year ago)
• Language: Python
• Homepage:
• Size: 9.77 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE-APACHE

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README

          
ml_params_xgboost

=================

![Python version range](https://img.shields.io/badge/python-3.6%E2%80%933.8+-blue.svg)

[![License](https://img.shields.io/badge/license-Apache--2.0%20OR%20MIT-blue.svg)](https://opensource.org/licenses/Apache-2.0)

[![Linting & testing](https://github.com/SamuelMarks/ml-params-xgboost/workflows/Linting%20&%20testing/badge.svg)](https://github.com/SamuelMarks/ml-params-xgboost/actions)

[xgboost [scikit.learn]](https://scikit-learn.org) implementation of ml-params CLI API

## Install dependencies

    pip install -r requirements.txt

## Install package

    pip install .

## Usage

After installing as above, follow usage from https://github.com/SamuelMarks/ml-params

## Sibling projects

  - https://github.com/SamuelMarks/ml-params-jax

  - https://github.com/SamuelMarks/ml-params-trax

  - https://github.com/SamuelMarks/ml-params-flax

  - https://github.com/SamuelMarks/ml-params-keras

  - https://github.com/SamuelMarks/ml-params-tensorflow

  - https://github.com/SamuelMarks/ml-params-pytorch

## Related projects

  - https://github.com/SamuelMarks/ml-prepare

---

## License

Licensed under either of

- Apache License, Version 2.0 ([LICENSE-APACHE](LICENSE-APACHE) or )

- MIT license ([LICENSE-MIT](LICENSE-MIT) or )

at your option.

### Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted

for inclusion in the work by you, as defined in the Apache-2.0 license, shall be

dual licensed as above, without any additional terms or conditions.