weka is a java based machine learning workbench that i’ve found useful to playing with to help understand some standard machine learning algorithms. in this quick demo i show how to build a classifier for three simple datasets; two of which address the basics of text classification
brutally short intro to weka from Mat Kelcey on Vimeo.
here’s a great lecture from tom mitchell about document classification using a semi supervised version of naive bayes.
semi supervised algorithms only require some of the training examples to be labeled and are able to make use of any unlabelled ones, very common when we have a huge corpus.
i’ve started an experiment brewing to test this out by porting some previous naive bayes work i did to use this semi supervised scheme and will published it when it’s done.
cool stuff!!
i’m amazed by how much great content is on youtube, how could you NOT learn something!?
