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MultiLabel-Transformer(MLE) is an extended version of a LabelEncoder, such that, it encodes multiple categorical columns to numeric in any workflow or pipeline

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MultiLabel-Transformer

MultiLabel-Transformer is an extended version of a LabelEncode, such that, it encodes multiple categorical columns to numeric in any workflow or pipeline. It was built upon Sciki-learn and distributed under the GPL-3.0 License.

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Installation Dependencies

MultiLabel-Transformer requires:

  • Python (>= 3.6)
  • scikit-learn(>=0.23.2)
  • pandas(>= 1.1.2)

Installation

Use pip to install, if you already have a working installation of sckit-learn and pandas
pip install -U MultiLabel_Transformer

ELSE if you have conda:

conda install MultiLabel_Transformer

How To Use

to be filled...

Development

We welcome new contributors of all experience levels.

Important links

  • Download releases: here
  • Issue tracker: here
  • Official source code repo: here

Contributing:

Interested in contributing?

well then, fork, clone and started!!

Help and Support

Documentation, Code Refinery and Improvements

Acknowedgement:

Special thanks to WorldQuant University and Udacity:AWS Scholarship, for their awesome lecture content.

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MultiLabel-Transformer(MLE) is an extended version of a LabelEncoder, such that, it encodes multiple categorical columns to numeric in any workflow or pipeline

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