Thanks Sean. I'll check with you for questions regarding Recommenders. Thanks for the pointer Isabel. I'll probably start off with https://cwiki.apache.org/MAHOUT/quickstart.html and make sure the examples and steps mentioned there works well. For example, the wikipedia bayes example references a build-deprecated.xml which I couldnt find anywhere. Once the example steps are cleaned out for the current version of Mahout, I'll start on each of quickstart/clustering , quickstart/classifying and so on.
For wikipedia bayes example, I am assuming that we need to download data (like how we are doing for Twenty Newsgroup example). can someone plz reference me the link or the process of getting this data ? thanks Joe. On Fri, Aug 13, 2010 at 5:30 AM, Isabel Drost <[email protected]> wrote: > On Fri, 13 Aug 2010 Joe Kumar <[email protected]> wrote: > > I am thinking of starting off with 1 classification (probably Naive > > Bayes) and create a template for the documentation like > > 1. Overview of the Algo > > 2. I/P data set (how to prepare and sample data set) > > 3. Maybe a sequence diagram explaining how the code flow happens (or > > any other way of representing this info ??) > > 4. O/P (how to read the o/p model and apply it for a real-world > > classification problem) > > You might also want to have a look at our Quickstart and Algorihtms > pages in the wiki and potentially simply extend those: > > Quickstart: > https://cwiki.apache.org/MAHOUT/quickstart.html > > Classification Overview: > https://cwiki.apache.org/MAHOUT/classifyingyourdata.html > > Brief explanation of Naive Bayes including links to examples: > https://cwiki.apache.org/MAHOUT/bayesian.html > > Isabel >
