NOTE: skutil is now deprecated. See its sister project: https://github.com/tgsmith61591/skoot. Original description: A set of scikit-learn and h2o extension classes (as well as caret classes for python). See more here: https://tgsmith61591.github.io/skutil
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Note: skutil has been deprecated and will no longer be supported. See its new sister project: skoot



h2o-sklearn

scikit-util

What began as a modest, succinct set of sklearn extension classes and utilities (as well as implementations of preprocessors from R packages like caret) grew to bridge functionality between sklearn and H2O. Now, scikit-util (skutil) brings the best of both worlds to H2O and sklearn, delivering an easy transition into the world of distributed computing that H2O offers, while providing the same, familiar interface that sklearn users have come to know and love. View the documentation here

Pre-installation

Skutil adapts code from several R packages, and thus depends on the ability to compile Fortran code using gcc. For different platforms, there are different ways to install gcc (the easiest, of course, being Homebrew):

  • Mac OS (note: this can take a while):
$ brew install gcc

There is a bug in some setups that will still cause issues in symlinking the gcc files via homebrew. If this is the case, the following line should clear things up:

$ brew link --overwrite gcc
  • Linux:
$ sudo apt-get install gcc

Installation:

Installation is easy. After cloning the project onto your machine and installing the required dependencies, simply use the setup.py file:

$ git clone https://github.com/tgsmith61591/skutil.git
$ cd skutil
$ python setup.py install

Testing

After installation, you can launch the test suite from outside the source directory (you will need to have the nose package installed):

$ nosetests -v skutil

Examples: