A powerful Automated Machine Learning python library.
Project description
MLBox, Machine Learning Box
===========================
.. -*- mode: rst -*-
|Documentation Status|_ |PyPI version|_ |Build Status|_ |GitHub Issues|_ |codecov|_ |License|_
.. |Documentation Status| image:: https://readthedocs.org/projects/mlbox/badge/?version=latest
.. _Documentation Status: http://mlbox.readthedocs.io/en/latest/?badge=latest
.. |PyPI version| image:: https://badge.fury.io/py/mlbox.svg
.. _PyPI version: https://pypi.org/project/mlbox/
.. |Build Status| image:: https://travis-ci.org/AxeldeRomblay/MLBox.svg?branch=master
.. _Build Status: https://travis-ci.org/AxeldeRomblay/MLBox
.. |GitHub Issues| image:: https://img.shields.io/github/issues/AxeldeRomblay/MLBox.svg
.. _GitHub Issues: https://github.com/AxeldeRomblay/MLBox/issues
.. |codecov| image:: https://codecov.io/gh/AxeldeRomblay/MLBox/branch/master/graph/badge.svg
.. _codecov: https://codecov.io/gh/AxeldeRomblay/MLBox
.. |License| image:: https://img.shields.io/badge/License-BSD%203--Clause-blue.svg
.. _License: https://github.com/AxeldeRomblay/MLBox/blob/master/LICENSE
**MLBox is a powerful Automated Machine Learning python library.**
* *It is compatible with:* **Python 2.7, 3.4 - 3.6**. & **64-bit version only** (32-bit python is not supported)
* *Operating system:* **Linux**. (MacOS & Windows very soon...)
Preparation
-----------
First, make sure you have `setuptools <https://pypi.python.org/pypi/setuptools>`__ installed. Since MLBox package contains C++ source code, check that the following requirements are installed:
* `gcc <https://gcc.gnu.org/>`__
.. code-block:: console
$ sudo apt-get install build-essential
* `cmake <https://cmake.org/>`__
.. code-block:: console
$ pip install cmake
Stable version
--------------
Install from pip
~~~~~~~~~~~~~~~~
MLBox is now available on **PyPI**, so you only need to run the following command:
.. code-block:: console
$ pip install mlbox
Install from the Github
~~~~~~~~~~~~~~~~~~~~~
* **The sources for MLBox can be downloaded** from the `Github repo`_.
* You can either clone the public repository:
.. code-block:: console
$ git clone git://github.com/AxeldeRomblay/mlbox
* Or download the `tarball`_:
.. code-block:: console
$ curl -OL https://github.com/AxeldeRomblay/mlbox/tarball/master
* Once you have a copy of the source, **you can install it:**
* Using setup.py:
.. code-block:: console
$ cd python-package/
$ python setup.py install
* Or directly, from the wheel:
.. code-block:: console
$ cd python-package/dist/
$ pip install *.whl
.. _Github repo: https://github.com/AxeldeRomblay/mlbox
.. _tarball: https://github.com/AxeldeRomblay/mlbox/tarball/master
Dev version
-----------
A **4.0 dev-version for MLBox is also available** on the branch `"4.0-dev" <https://github.com/AxeldeRomblay/MLBox/tree/4.0-dev>`__ ! It provides some interesting new features. Please refer to `HISTORY <https://github.com/AxeldeRomblay/MLBox/blob/master/HISTORY.rst>`__.
**It depends on sklearn-0.19.dev0 which is not a stable version at the moment.**
===========================
.. -*- mode: rst -*-
|Documentation Status|_ |PyPI version|_ |Build Status|_ |GitHub Issues|_ |codecov|_ |License|_
.. |Documentation Status| image:: https://readthedocs.org/projects/mlbox/badge/?version=latest
.. _Documentation Status: http://mlbox.readthedocs.io/en/latest/?badge=latest
.. |PyPI version| image:: https://badge.fury.io/py/mlbox.svg
.. _PyPI version: https://pypi.org/project/mlbox/
.. |Build Status| image:: https://travis-ci.org/AxeldeRomblay/MLBox.svg?branch=master
.. _Build Status: https://travis-ci.org/AxeldeRomblay/MLBox
.. |GitHub Issues| image:: https://img.shields.io/github/issues/AxeldeRomblay/MLBox.svg
.. _GitHub Issues: https://github.com/AxeldeRomblay/MLBox/issues
.. |codecov| image:: https://codecov.io/gh/AxeldeRomblay/MLBox/branch/master/graph/badge.svg
.. _codecov: https://codecov.io/gh/AxeldeRomblay/MLBox
.. |License| image:: https://img.shields.io/badge/License-BSD%203--Clause-blue.svg
.. _License: https://github.com/AxeldeRomblay/MLBox/blob/master/LICENSE
**MLBox is a powerful Automated Machine Learning python library.**
* *It is compatible with:* **Python 2.7, 3.4 - 3.6**. & **64-bit version only** (32-bit python is not supported)
* *Operating system:* **Linux**. (MacOS & Windows very soon...)
Preparation
-----------
First, make sure you have `setuptools <https://pypi.python.org/pypi/setuptools>`__ installed. Since MLBox package contains C++ source code, check that the following requirements are installed:
* `gcc <https://gcc.gnu.org/>`__
.. code-block:: console
$ sudo apt-get install build-essential
* `cmake <https://cmake.org/>`__
.. code-block:: console
$ pip install cmake
Stable version
--------------
Install from pip
~~~~~~~~~~~~~~~~
MLBox is now available on **PyPI**, so you only need to run the following command:
.. code-block:: console
$ pip install mlbox
Install from the Github
~~~~~~~~~~~~~~~~~~~~~
* **The sources for MLBox can be downloaded** from the `Github repo`_.
* You can either clone the public repository:
.. code-block:: console
$ git clone git://github.com/AxeldeRomblay/mlbox
* Or download the `tarball`_:
.. code-block:: console
$ curl -OL https://github.com/AxeldeRomblay/mlbox/tarball/master
* Once you have a copy of the source, **you can install it:**
* Using setup.py:
.. code-block:: console
$ cd python-package/
$ python setup.py install
* Or directly, from the wheel:
.. code-block:: console
$ cd python-package/dist/
$ pip install *.whl
.. _Github repo: https://github.com/AxeldeRomblay/mlbox
.. _tarball: https://github.com/AxeldeRomblay/mlbox/tarball/master
Dev version
-----------
A **4.0 dev-version for MLBox is also available** on the branch `"4.0-dev" <https://github.com/AxeldeRomblay/MLBox/tree/4.0-dev>`__ ! It provides some interesting new features. Please refer to `HISTORY <https://github.com/AxeldeRomblay/MLBox/blob/master/HISTORY.rst>`__.
**It depends on sklearn-0.19.dev0 which is not a stable version at the moment.**
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