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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.

Project description

Data Scaler Selector

Author MIT Contributions welcome Stars

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

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

License

License: 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

Project details


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DataScalerSelector-1.0.9.tar.gz (14.5 MB view hashes)

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