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Nak

Author: Jason Baldridge (jasonbaldridge@gmail.com)

Introduction

Nak is a library for machine learning and related tasks. It is formed from the OpenNLP Maxent package, and my intent is to evolve it as a Scala library with further capabilities. It will be developed in particular with the natural language processing library Chalk in mind.

Like Chalk, the name Nak comes from one of my son's stuffed elephants. (He really likes elephants.)

Using Nak

The latest stable release is 1.0, which corresponds quite directly to the Maxent part of Apache OpenNLP v1.5.3.

In SBT:

libraryDependencies += "com.jasonbaldridge" % "nak" % "1.0"

In Maven:

<dependency>
   <groupId>com.jasonbaldridge</groupId>
   <artifactId>nak</artifactId>
   <version>1.0</version>
</dependency>

Requirements

Configuring your environment variables

The easiest thing to do is to set the environment variables JAVA_HOME and NAK_DIR to the relevant locations on your system. Set JAVA_HOME to match the top level directory containing the Java installation you want to use.

Next, add the directory NAK_DIR/bin to your path. For example, you can set the path in your .bashrc file as follows:

export PATH=$PATH:$NAK_DIR/bin

Once you have taken care of these three things, you should be able to build and use Nak.

Building the system from source

Nak uses SBT (Simple Build Tool) with a standard directory structure. To build Nak, type (in the $NAK_DIR directory):

$ ./build update compile

This will compile the source files and put them in ./target/classes. If this is your first time running it, you will see messages about Scala being downloaded -- this is fine and expected. Once that is over, the Nak code will be compiled.

To try out other build targets, do:

$ ./build

This will drop you into the SBT interface. To see the actions that are possible, hit the TAB key. (In general, you can do auto-completion on any command prefix in SBT, hurrah!)

To make sure all the tests pass, do:

$ ./build test

Documentation for SBT is at http://www.scala-sbt.org/

Note: if you have SBT already installed on your system, you can also just call it directly with "sbt" in NAK_DIR.

Questions or suggestions?

Email Jason Baldridge: jasonbaldridge@gmail.com

Or, create an issue: https://github.com/jasonbaldridge/nak/issues

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The Nak Machine Learning Library

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