semvec/pypi-packages huggingface dataset:
fets 0.5.3
Feature Engineering Transformer Set
License: BSD
Requires Python: >=3
Keywords: data,feature-engineering,feature-extraction,machine-learning,transformer,transformation,pipeline

FETS
=====

[![pipeline status](https://gitlab.com/redsharpbyte/fets/badges/master/pipeline.svg)](https://gitlab.com/redsharpbyte/fets/commits/master)
[![coverage report](https://gitlab.com/redsharpbyte/fets/badges/master/coverage.svg)](https://gitlab.com/redsharpbyte/fets/commits/master)



Set of ready-to-use transformers for your feature engineering pipelines in scikit-learn.

Inspired by the number of times I had to rewrite transformers and by the number 
of times we all did exactly the same.


How-To
======

TODO



Installation
============

```
red@spaceport# pip install fets
```

Testing
=======

```
red@spaceport# cd fets/
red@spaceport# pytest -v tests
```