Building the classification models could actually be an interesting exercise for clustering as much as for classification.
The steps could be: a) cluster into 2x necessary number of clusters b) label each cluster according to a CL-derived category c) mark positive and negative examples in the cluster according to labels applied in (b) d) train on labeled examples, possibly run a cluster step starting from the trained models On Thu, Jan 21, 2010 at 11:42 AM, Jason Rutherglen < [email protected]> wrote: > 2) Get all #forsale Tweets via the Twitter streaming API > > 3) Manually build the classification models (this is where tools > will aka a workbench will help) > -- Ted Dunning, CTO DeepDyve
