Hi Daniel, do you see any issue if we expose LLThreshold and allow the user to change it via training parameters?
Jörn On Sat, Aug 26, 2017 at 1:07 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 .” * >>> >
