sklearn-ranking 0.0.1

This package is used for recommendation system

[](https://dev.azure.com/imbalanced-learn/imbalanced-learn/_build) [](https://travis-ci.org/scikit-learn-contrib/imbalanced-learn) [ ](https://codecov.io/gh/scikit-learn-contrib/imbalanced-learn)[](https://circleci.com/gh/scikit-learn-contrib/imbalanced-learn/tree/master) [ ](https://img.shields.io/pypi/pyversions/imbalanced-learn.svg)[ ](https://badge.fury.io/py/imbalanced-learn)[](https://gitter.im/scikit-learn-contrib/imbalanced-learn?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)

## sklearn-ranking

sklearn-ranking is a python package offering a ranking algorithm.

### Installation

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#### Dependencies

imbalanced-learn is tested to work under Python 3.6+. The dependency requirements are based on the last scikit-learn release:

• scipy(>=0.19.1)

• numpy(>=1.13.3)

• scikit-learn(>=0.22)

• joblib(>=0.11)

• keras 2 (optional)

• tensorflow (optional)

Additionally, to run the examples, you need matplotlib(>=2.0.0) and pandas(>=0.22).

#### Installation

imbalanced-learn is currently available on the PyPi’s repository and you can install it via pip:

` pip install -U sklearn-ranking `

The package is release also in Anaconda Cloud platform:

` conda install -c conda-forge sklearn-ranking `

If you prefer, you can clone it and run the setup.py file. Use the following commands to get a copy from GitHub and install all dependencies:

` git clone https://github.com/ashishpatel26/sklearn-ranking.git cd sklearn-ranking pip install . `

Or install using pip and GitHub:

` pip install -U git+https://github.com/ashishpatel26/sklearn-ranking.git `