semvec/pypi-packages huggingface dataset:
Beat-ML1 0.13.1
This package contains several methods for calculating Conditional Average Treatment Effects
License: MIT
Keywords: treatment-effect

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<h1><img src="doc/econml-logo-icon.png" width="80px" align="left" style="margin-right: 10px;"> BEAT: A Python Package for ML-Based Heterogeneous Treatment Effects Estimation</h1>

**BEAT** is a Python package for estimating heterogeneous treatment effects from observational data via machine learning:

* All arguments are the same as the original package, but there are two new inputs: target.weight.penalty indicates the penalty assigned to the protected attributes. target.weights is a matrix that includes the protected characteristics. X should not inlcude the protected characteristics. 
* See full details about the BEAT method in the original paper: Eliminating unintended bias in personalized policies using bias-eliminating adapted trees (BEAT)
* Forked from https://github.com/Microsoft/EconML


# Getting Started

## Installation

Install the latest release from [PyPI](https://pypi.org/project/BEAT_TEST/):
```
pip install BEAT_TEST
```
## Usage Examples
### Estimation Methods

  ```Python
  from econml.grf import BeatForest
  #Setting Training treatment and outcome 
  treatment = ['W']
  outcome = ['Y']
  Y = train[outcome]
  T = train[treatment]
  #Setting Unprotected variables
  unprotected_covariate = ['X.V1', 'X.V2', 'X.V3', 'X.V4', 'X.V5', 'Z.V1', 'Z.V2', 'Z.V3', 'Z.V4']
  X1 = train[unprotected_covariate]
  #set parameters for BEAT and Fit in training values
  BEAT = BeatForest(alpha = 10, demean = 0, n_estimators = 8)                     
  BEAT.fit(X1, T, Y) 
  #Get prediction from test dataset
  prediction = BEAT.predict(X_test)
```

# References
Ascarza, E., &amp; Israeli, A. (2022). Eliminating unintended bias in personalized policies using bias-eliminating adapted trees (beat). Proceedings of the National Academy of Sciences, 119(11). https://doi.org/10.1073/pnas.2115293119
gitflic-bb 1.112
GitflicApi-bb wrapper
License: MIT
Requires Python: >=3.7

# gitflic

<p align="center">
    <a href="https://github.com/SantaSpeen/gitflic/blob/master/LICENSE"><img alt="GitHub license" src="https://img.shields.io/github/license/SantaSpeen/gitflic?style=for-the-badge"></a>    
    <a href="https://github.com/SantaSpeen/gitflic/stargazers"><img alt="GitHub stars" src="https://img.shields.io/github/stars/SantaSpeen/gitflic?style=for-the-badge"></a>    
    <a href="https://github.com/SantaSpeen"><img src="https://img.santaspeen.ru/github/magic.svg" alt="magic"></a>
    <br/>
    <a href="examples/reg_call.py">
        <img src="https://img.santaspeen.ru/github/gitflic/preview.png" alt="preview">
    </a>
    <br/>
</p>

### About 

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This is wrapper of gitflic API.\
All API documentation is here: https://gitflic.ru/help/api/intro

### Installation

Install via pip:

```shell
# Shell

$ pip3 install gitflic
```

### Example:

All examples in [examples](./examples) dir.

```python
from gitflic import Gitflic, GitflicAuth

# Your authentication token.
# See: https://gitflic.ru/settings/oauth/token/create
token = "token_here"  

# Creating authorized session with our token.
gf_session = GitflicAuth(token)
gf = Gitflic(gf_session)


# Call method to get authorized user from API.
user_me = gf.call("/user/me")
print(user_me)
```