I am new to apache mahout. I have managed to use it for pearson corelation and cosine vector but i need to normalize data and use Z Score to calculate similarity. I am unable to find methods in mahout which allow to do so. The mahout wiki also doesn't demonstrate the use of normalization of data and use for calculating similarity. I would be very thankful if someone can help me out with the code for the same.
These questions are better answered on the mahout user mailing list.
In any case, it would be nice to understand what you are trying to do on a larger scale. It sounds like you might be trying to build a recommendation engine. If so, Pearson correlation is generally a really bad way to do that.
It is much better to use Mahout to compute indicator behaviors and then use a search engine such as Solr or ElasticSearch to deploy the recommendation function.
We described how to do this in the O'Reilly small book that you can get from: