semvec/pypi-packages huggingface dataset:
DataScalerSelector 1.1.0
Data Scaler Selector is an open-source python library to select the appropriate data scaler (Min-Max, Robust or Standard Scaler) for your Machine Learning model.
Keywords: scaler

# Data Scaler Selector
![Author](https://img.shields.io/badge/author-aaneloy-blue)
[![MIT](https://img.shields.io/badge/license-MIT-5eba00.svg)](https://github.com/aaneloy/scaler_selector/blob/main/LICENSE.txt)
[![Contributions welcome](https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat)](https://github.com/aaneloy/scaler_selector)
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Data Scaler Selector is an open-source python library to select the appropriate data scaler (**Min-Max, Robust or Standard Scaler**) for your Machine Learning model.


## Author: [Asif Ahmed Neloy](https://aaneloy.netlify.app/)

## Project Description:
Data Scaler is an open-source python library to select the appropriate data scaler for your Machine Learning model.


## Installation:
```
pip install DataScalerSelector
```

## Sample Notebook
In order to run the ``scalerselector_regression`` the following must be ensured:
* ``NULL`` data must be handled
* There should be no categorical variable.
* Select the ``features X`` and ``Target variable y``
* After selecting ``X`` and ``y`` run the follwing:
```
from DataScalerSelector import *

scalerselector_regression(X,y)

```

For details see this [notebook](https://github.com/aaneloy/scaler_selector/blob/main/src/notebook/Sample.ipynb)

## License
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

Change Log
==========

1.0 (29/12/2021)
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- First Release

1.0.2 (29/12/2021)
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- Installation Fixed

1.0.3 (30/12/2021)
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- Installation Bug Fixed

1.0.4 (30/12/2021)
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- Dependency Fixed

1.0.5 (30/12/2021)
------------------
- Sample Test Added

1.0.6 (30/12/2021)
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- Minor Bug fixed

1.0.7 (30/12/2021)
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- Minor Bug fixed

1.0.8 (30/12/2021)
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- Sample Notebook added

1.0.9 (31/12/2021)
------------------
- Bug Fixed

1.1.0 (03/01/2022)
------------------
- Current Working Version