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From Daniel Russ <>
Subject Re: Early stopping NameFinderME
Date Fri, 25 Aug 2017 23:07:03 GMT

   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?


> On Aug 24, 2017, at 4:48 AM, Joern Kottmann <> 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" <> 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 .” *

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