Hi,
the score is the probability of the example belonging to the class but
under independence assumptions and hence only useful to compare scores of
different classes with each other (..more likely than..). Since it is meant
to be a probability, it can range from 0 to 1.
If you want to transform the score into probabilities, maybe "calibration"
of scores is something for you. Look at the following paper
http://www.bradblock.com/Transforming_Classifier_Scores_into_Accurate_Multiclass_Probability_Estimates.pdf
HAve a nice day,
Johannes
On Mon, Feb 25, 2013 at 6:52 AM, Seetha <abiramisethu@gmail.com> wrote:
>
>
> Ramprakash Ramamoorthy <youngestachiever <at> gmail.com> writes:
>
> >
> > Dear all,
> >
> > I am performing a sentiment analysis using the naive bayes
> > classifier on apache mahout. Every time when I get the result, I get a
> > category and a score corresponding to the score.
> >
> > Can some one here enlighten me on the score? Like what is
> the
> > maximum score for a given category(I have two categories  positive and
> > negative). So based on the score can I categorize them as very
> > positive,very negative etc. Any input regarding the same would be
> helpful.
> > Thank you.
> >
>
> Hi Ramprakash,
>
> Have you resolved the problem u mentioned earlier.
>
> Thank you.
>
>
