scikit-learn/scikit-learn — pull request #1194 by amueller (2012-09-30 20:26:30+00:00)
Title: WIP first draft of random sampling hyper parameters

This is another shot at implementing randomized hyper parameter search in sklearn.
In contrast to #455, I use scipy.stats distributions for each parameter.

If I understand James' Paper correctly, one of the important points is not to use a grid.
This way you have resolution everywhere.

For discrete parameters, the user can also specify a list of names i.e. ``kernel=['rbf', 'linear', 'poly']``, which is sampled from using a uniform distribution.

I don't like passing objects as parameters, but this seems to be the best way to specify a distribution.
A user can put in any object that supports ``.rvs()`` and scipy.stats.distributions already has a solid amount of predefined ones.