Hi Jorn

Let me explain you what I am trying to do. I have 3 categories and need to
create 3 different NameFinder model for each category. I train 3 models in
sequence (although each one is independent) with training step 1000. While
training on a specific category, lets say first category, if change in
likelihood values between two steps (differ by 5) is less than a threshold
then I would like stop training at that step and start training next
category and so on.

Your question: *can't you set the number of iterations in the training
properties*
No, I can't

@Joern
Issue has been created on Jira
https://issues.apache.org/jira/browse/OPENNLP-1123



On Sat, Aug 26, 2017 at 4:37 AM, Daniel Russ <[email protected]> wrote:

> Jörn,
>
>    Currently, GISTrainer has a private static final variable LLThreshold,
> which controls if the change in the log likelihood between two iterations
> is too small.  We could make this parameter. I am concerned about using the
> accuracy to train the model.  If we use accuracy, the weight space may be
> flat.
>
>    Saurabh, you use the term “early stopping”.  In deep learning, early
> stopping is used to prevent overtraining and improve generalization to
> unseen data.  I am not sure early stopping serves the same purpose with GIS
> training.  Does anyone know if early stopping improves generalization for a
> maxent problem?
>
> Daniel
>
> > On Aug 24, 2017, at 4:48 AM, Joern Kottmann <[email protected]> wrote:
> >
> > You are the first one who ever asked this question. I think we have this
> as
> > an option already on the gis trainer but it is not exposed all the way
> > through.
> >
> > Please open a jira and I can look at it next week.
> >
> > Jörn
> >
> > On Aug 21, 2017 5:11 PM, "Saurabh Jain" <[email protected]>
> wrote:
> >
> >> Hi All
> >>
> >> How can we use early stopping while training/crossvalidating custom data
> >> with NameFinder ? What I want if change in likelihood value or accuracy
> of
> >> model is less than 0.05 between two steps (differ by 5 i.e compare x+5
> step
> >> output with x step) then training should stop. I could not find anything
> >> regarding this in documentation. Can some one please help ?
> >>
> >> --
> >> *Thanks & Regards*
> >>
> >>
> >> *Saurabh Jain *
> >> *AI Developer*
> >>
> >> *Active Intelligence  *
> >>
> >> *"*
> >> *To do a thing yesterday was the best time . Second best time is today
> .” *
> >>
>
>


-- 
*Thanks & Regards*


*Saurabh Jain *
*AI Developer*

*Active Intelligence  *

*"*
*To do a thing yesterday was the best time . Second best time is today .” *

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