Hi Shirish,
Thanks for your clarification.
Not sure how exactly I can modify the GLMpredict.dml to get some
prediction to start with. Ideally I would like the probability threshold to
be parameterized.
If I check the script at line 135136 I can see the code which returns
means and vars 
[means, vars] = glm_means_and_vars (linear_terms, dist_type, var_power,
link_type, link_power);
Can you give me some idea how from here I can calculate the predicted value
of the label using some value of probability threshold ?
Regards,
Sourav
On Tue, Dec 8, 2015 at 12:49 PM, Shirish Tatikonda <
shirish.tatikonda@gmail.com> wrote:
> 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
> >
>
