Yes.
0 is perfect prediction. It can only be achieved by a score of 1 for the
correct answer every time.
Note that average loglikelihood only works for probability scores.
On Tue, May 31, 2011 at 6:38 PM, Xiaobo Gu <guxiaobo1982@gmail.com> wrote:
> On Tue, May 31, 2011 at 11:54 PM, Ted Dunning <ted.dunning@gmail.com>
> wrote:
> > Argh....
> >
> > loglikelihood should approach the percentage of INcorrect answers
> > (negated).
>
> Then we just only to see if the average log likeliyhood is closer to 0
> to determine the perfmonce of the model, regardless the relationship
> between it and percentage of INcorrect or correct answers?
>
>
> > On Tue, May 31, 2011 at 7:49 AM, Xiaobo Gu <guxiaobo1982@gmail.com>
> wrote:
> >
> >> Page 228 of version 7 of Mahout in Action says :
> >>
> >> Loglikelihood has a maximum value of zero and no bound on how far
> >> negative it can go. For highly accurate classifiers, the value of
> >> average loglikelihood should be close to the average percent correct
> >> for the classifier times the number of target categories.
> >>
> >> Average percent correct times the number of target categories is more
> >> than 0, while Loglikelihood is always less than 0, then is the above
> >> statement correct ?
> >>
> >>
> >>
> >> On Tue, May 31, 2011 at 10:45 PM, Xiaobo Gu <guxiaobo1982@gmail.com>
> >> wrote:
> >> > Does it mean the percent of records that the model has correctlly
> >> > predicted the target on the validate protion of the data set, then it
> >> > should be between 0 and 1, and the bigger the better performance of
> >> > the model ?
> >> >
> >> > Regards,
> >> >
> >> > Xiaobo Gu
> >> >
> >>
> >
>
