Metadata-Version: 2.1
Name: DataScalerSelector
Version: 1.0.9
Summary: 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.
Home-page: https://github.com/aaneloy/data-scaler
Author: Asif Ahmed Neloy
Author-email: neloyn@myumanitoba.ca
License: UNKNOWN
Keywords: scaler
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: LICENSE.txt

# 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/AmitHasanShuvo/data-inspector/blob/main/LICENCE.txt)
[![Contributions welcome](https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat)](https://github.com/AmitHasanShuvo/data-inspector)
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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)
------------------
- First Release

1.0.2 (29/12/2021)
------------------
- Installation Fixed

1.0.3 (30/12/2021)
------------------
- Installation Bug Fixed

1.0.4 (30/12/2021)
------------------
- Dependency Fixed

1.0.5 (30/12/2021)
------------------
- Sample Test Added

1.0.6 (30/12/2021)
------------------
- Minor Bug fixed

1.0.7 (30/12/2021)
------------------
- Minor Bug fixed

1.0.8 (30/12/2021)
------------------
- Sample Notebook added

1.0.9 (31/12/2021)
------------------
- Current Working Version








