An article was written a while back about how neural networks can be used to classify source code. Yes the source code that you write to feed to compilers / interpreters.
The article explains at a high level what method could be used to perform this activity. In the end the author claims some level of success and wonders how other neural-network implementations / techniques would solve the same problem. This got me curious enough and I spent a weekend trying to crack this with Neuroph, the neural network library for java. I present to you my analysis and results below. For the impatient here is the code-classifier DEMO.
The java neural network Neuroph was making news recently about its integration with Hadoop. Neural networks can solve some interesting problems once they are trained. This article aims to provide the baby steps necessary to writing your first java program that loads a trained neural network.
Before you even begin to read anything that follows, a basic understanding of neural network terminology and the concept behind the same is necessary. The following articles are great starting points to understanding neural networks
Neuroph and neural networks – Part 1
Neuroph and neural networks – Part 2
Neuroph and neural networks – Part 3
Intro to neural networks
Cars and Signals:
We will simulate the scenario where cars wait at a signal and move only when the lights are green. This simple example should help get you started. Our aim is to define a neural network with the easyNeurons swing application; train it; import it into java and use it in an application.