murphy

This is a library for structured prediction. It was primarily developed by Taylor Berg-Kirkpatrick. Other contributors include John DeNero, Aria Haghighi, Dan Klein, Jonathan Kummerfeld, and Adam Pauls.

To use the library, download it one of these ways, and include it in your code as described below:

This library was initially released as supplementary material for the experiments described in:

An Empirical Analysis of Optimization for Max-Margin NLP, Jonathan K. Kummerfeld, Taylor Berg-Kirkpatrick and Dan Klein, EMNLP 2015

Using the library

You will need to implement the following:

Then include this code on your classpath, compile, and you're ready to go!

For an exmple, see the files in the example directory. Note, the classification it does is trivial, but it shows how you put the pieces together. You can build and run the example with build_and_run_example.sh (assuming you have javac, java, and standard command line tools - find, echo, mkdir).

Options

The library comes with three versions of the structured predicition code:

Note that the dual methods (NSlackSVMLearner) are only implemented for the basic version.