In theory, what you need to do is take your training data for your classifier and run your clustering to get a 1 of n encoding of the cluster for each example in the training data.
Then train the classifier using original and new features. Does that help? I have a simple demo of the process in R that I do if that would help. On Mon, May 5, 2014 at 5:53 PM, Angel Luis Scull <[email protected]>wrote: > Hello to all > > I've a document dataset that I applied kmeans over it an obtained a > clusters, now I want to use this the association of the vectors and > clusters as input for a classification algorithm. > > How can I achieve that? > > thanks in advance >
