Name | eazyml-xai JSON |
Version |
0.0.45
JSON |
| download |
home_page | https://eazyml.com/ |
Summary | Python client for Explainable AI |
upload_time | 2025-01-10 16:43:13 |
maintainer | None |
docs_url | None |
author | Eazyml |
requires_python | >=3.8 |
license | None |
keywords |
python
|
VCS |
|
bugtrack_url |
|
requirements |
No requirements were recorded.
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Travis-CI |
No Travis.
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coveralls test coverage |
No coveralls.
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## Eazyml Explainable AI
![Python](https://img.shields.io/badge/python-3.7%20%7C%203.8%20%7C%203.9%20%7C%203.10%20%7C%203.11%20%7C%203.12-blue) ![PyPI package](https://img.shields.io/badge/pypi%20package-0.0.45-brightgreen) ![Code Style](https://img.shields.io/badge/code%20style-black-black)
![EazyML](https://eazyml.com/static/media/EazyML%20XAI%20blue.b7696b7a.png)
It provides explanations for a model's prediction, based on provided train and test data files.
### Features
- It provides explanations for a model's prediction, based on provided train and test data files.
### APIs
It provides following apis :
1. scikit_feature_selection
```python
ez_explain(
mode='classification',
outcome='target',
train_file_path='train.csv',
test_file_path='test.csv',
model=my_model,
data_type_dict=data_type_dict,
selected_features_list=lis_of_derived_features,
options={"data_source": "parquet", "record_number": [1, 2, 3]})
### Useful Links
- [Documentation](https://docs.eazyml.com)
- [Homepage](https://eazyml.com)
- If you have more questions or want to discuss a specific use case please book an appointment [here](https://eazyml.com/trust-in-ai)
#### License
This project is licensed under the [Proprietary License](https://github.com/EazyML/eazyml-docs/blob/master/LICENSE).
---
*Maintained by [EazyML](https://eazyml.com)*
*© 2025 EazyML. All rights reserved.*
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