Hi Martin,
  Indeed weka supports calculation of such probability estimates, but is
it possible to obtain some confidence interval estimation for a
regresssion model, i.e. upper and lower bounds imposed on the predicted
value for a given confidence level. I haven't found such an option
yet...

Regards,
Pantelis

On Tue, 2010-03-23 at 16:43 +0100, Martin Guetlein wrote:
> Dear Harry, All,
> 
> WEKA computes a propability distribution for each instance when
> performing classification. I couldn't find any documentation in the
> manual, here is what I know:
> 
> The distribution depends on the classifier, and is supported by some
> non-probabilistic classifiers as well (e.g. Nearest Neighbor, the
> distribution corresponds to the numbers of neighbors for each class).
> Other classifiers that do not support any confidence/probability (e.g.
> SMO) simply return 1 for the predicted class value, 0 for the other
> class values.
> 
> Using the command line you can use -p to output the distribution
> instead of the predicted class.
> 
> When using the Java API:
> 
> Evaluation evaluation = new Evaluation( trainDataset );
> evaluation.evaluateModel( classifier, testDataset );
> for (int i = 0; i < evaluation.predictions(); i++) {
>   NominalPrediction prediction = (NominalPrediction)
> evaluation.predictions().elementAt(i);
>   double[] distribution = prediction.distribution();
> }
> 
> Best regards,
> Martin
> 
> 
> On Tue, Mar 23, 2010 at 2:57 PM, Haralambos Sarimveis
> <hsarimv at central.ntua.gr> wrote:
> > Hello Martin,
> >
> >
> >
> > You mentioned during yesterday’s discussion that all WEKA algorithms can
> > produce confidence intervals for the predictions. Can you please give some
> > reference?
> >
> >
> >
> > Best regards,
> >
> > Harry
> >
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> 
> 
>