Hi Sourav,
Yes, GLMpredict.dml gives out only the probabilities. You can put a
threshold on the resulting probabilities to get the actual class labels 
for example, prob > 0.5 is positive and <=0.5 as negative.
The exact value of threshold typically depends on the data and the
application. Different thresholds yield different classifiers with
different performance (precision, recall, etc.). You can find the best
threshold for the given data set by finding a value that gives the desired
classifier performance (for example, a threshold that gives roughly equal
precision and recall). Such an optimization is obviously done during the
training phase using a held out test set.
If you wish, you can also modify the DML script to perform this entire
process.
Shirish
On Tue, Dec 8, 2015 at 12:23 PM, Sourav Mazumder <
sourav.mazumder00@gmail.com> wrote:
> Hi,
>
> I have used GLM.dml to create a model using some sample data. It returns to
> me the matrix of Beta, B.
>
> Now I want to use this matrix of Beta on a new set of data points and
> generate predicted value of the dependent variable/observation.
>
> When I checked GLMpredict, I could see that one can pass feature vector
> for the new data set and also the matrix of beta.
>
> But I could not see any way to get the predicted value of the dependent
> variable/observation. The output parameter only supports matrix of
> predicted means/probabilities.
>
> Is there a way one can get the predicted value of the dependent
> variable/observation from GLMpredict ?
>
> Regards,
> Sourav
>
