I have been playing around the NLTK algorithm for some data prediction.
Starting from this gib, I started my understanding process. However, there are some bits that don't make sense.
If I have a set of 100 features, all classified, what's the sense to split them, take 10% and build the training set on that alone? I thought the training set should have included all the list, and accuracy is measured against the new keywords being tested against?
Any hint would be helpful.