Thank you for clarifying this point for me!
2016-05-13 13:53 GMT-04:00 Bertrand Dechoux <decho...@gmail.com>: > The decision rule being "the result is the one with the highest > probability", it is possible to avoid computation so that this previous > decision rule is equivalent to "the result is the one with highest score", > as long as the mathematical transformation from probability to score to not > change the top class. > > > > Bertrand Dechoux > > On Thu, May 12, 2016 at 4:40 AM, Andrew Palumbo <ap....@outlook.com> > wrote: > > > Hello, the elements of the vector are not actually probabilities, they > are > > scores, the classification is a winner takes all approach, assigning the > > classification to the class with the max score. > > > > See: http://mahout.apache.org/users/algorithms/spark-naive-bayes.html > for > > an overview of the algorithm. > > > > Thanks > > > > ________________________________________ > > From: Nantia Makrynioti <nantiam...@gmail.com> > > Sent: Wednesday, May 11, 2016 10:33:29 PM > > To: user@mahout.apache.org > > Subject: Negative probabilities > > > > Hello, > > > > I am using the classifyFullInstance method on a Naive Bayes model, but > when > > I print the elements of the generated vector, the probabilities are > > negative. What might be the reason for this? > > > > Thanks a lot, > > Nantia > > >
