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| -rw-r--r-- | README.markdown | 25 |
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diff --git a/README.markdown b/README.markdown index 2b731c8..bb50aae 100644 --- a/README.markdown +++ b/README.markdown @@ -1,9 +1,8 @@ -PyFeast -==== +# PyFeast + Python bindings to the FEAST Feature Selection Toolbox -About PyFeast -============= +## About PyFeast PyFeast is a interface for the FEAST feature selection toolbox, which was originally written in C with a interface to matlab. @@ -16,16 +15,14 @@ At Drexel University's EESI Lab (link), we are using PyFeast to create a feature selection tool for the Department of Energy's upcoming KBase platform. -Requirements -============ +## Requirements In order to use the feast module, you will need the following dependencies * Python 2.7 * Numpy * Linux or OS X -Installation -============ +## Installation To install the FEAST interface, you'll need to build and install the libraries first, and then install python. @@ -47,17 +44,13 @@ $ python ./setup.py build $ sudo python ./setup.py install -Demonstration -============= +## Demonstration See test/test.py for an example with uniform data and an image data set. The image data set was collected from the digits example in the Scikits-Learn toolbox. -References -========== -* [FEAST](http://www.cs.man.ac.uk/~gbrown/fstoolbox/) - - The Feature Selection Toolbox -* [Fizzy](http://www.kbase.us/developer-zone/api-documentation/fizzy-feature-selection-service/) - - A KBase Service for Feature Selection +## References +* [FEAST](http://www.cs.man.ac.uk/~gbrown/fstoolbox/) - The Feature Selection Toolbox +* [Fizzy](http://www.kbase.us/developer-zone/api-documentation/fizzy-feature-selection-service/) - A KBase Service for Feature Selection * [Conditional Likelihood Maximisation: A Unifying Framework for Information Theoretic Feature Selection] (http://jmlr.csail.mit.edu/papers/v13/brown12a.html) |