Posts and notes Weka

A couple of years ago I wrote a blog post about wrapping some of Weka’s classification functionality to allow it to be used programmatically in Python programs. A small project I’m currently working on at home is around taking some of the later research from my PhD work to see if it can be expressed and used as a simple web-app.

I began development in Go as I hadn’t yet spent much time working with the language. The research work involves using a Bayesian network classifier to help infer a tweet’s interestingness, and while Go machine-learning toolkits do exist, I wanted to use my existing models that were serialized in Java by Weka.

Over the last few months, I’ve started to use Weka more and more. Weka is a toolkit, written in Java, that I use to create models with which to make classifications on data sets.

It features a wide variety of different machine learning algorithms (although I’ve used the logistic regressions and Bayesian networks most) which can be trained on data in order to make classifications (or ‘predictions’) for sets of instances.