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From Nantia Makrynioti <nantiam...@gmail.com>
Subject Re: Negative probabilities
Date Sat, 14 May 2016 23:27:29 GMT
Thank you for clarifying this point for me!



2016-05-13 13:53 GMT-04:00 Bertrand Dechoux <dechouxb@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.dev@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 <nantiamakr@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
> >
>

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