easypredict

generic predictive framework to evaluate predictive power of arbitrary feature to target mapping

These details have not been verified by PyPI

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Project description

generic predictive framework to evaluate predictive power of arbitrary feature to target mapping

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

0.0.1 (2018-05-16)

These details have not been verified by PyPI

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

This version

0.0.1

May 16, 2018

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Uploaded May 16, 2018 Source

Uploaded May 16, 2018 Python 2 Python 3

Hashes for easypredict-0.0.1.tar.gz
Algorithm	Hash digest
SHA256	`3b90859d2166cc8c7303b993d227a7ebdce055cd778f45ea2bd8430b58b56e22`
MD5	`100a95a80769b6b270dfa5a738192f6c`
BLAKE2b-256	`0aefdbbc14b23bba19ae9ab3490be981068fb724c5e7ea8fd467e4d28986e60e`

Hashes for easypredict-0.0.1-py2.py3-none-any.whl
Algorithm	Hash digest
SHA256	`2a7a0a31643d0357ac3e37c67d1a020c06d60cb7dcbb414d2b1823ddd366bc82`
MD5	`0fb81727809f97e0ec86279fa11bf19d`
BLAKE2b-256	`7ae49fa9e71bf79aa5491307ec22aa4aa77dd18e0c5c4898e0a8f2d7bf2e4523`