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Published 20 hours ago • verified publisher icon tensorflow

Class-Balanced Loss Based on Effective Number of Samples

Open ashutosh1919 opened this issue 2 years ago • 2 comments

Currently, TensorFlow has Focal loss which can be one of the options to handle the class imbalance issues. But I myself have faced problems in the case of some datasets like RecSys. IMO, TensorFlow should consist of Class-balanced loss (paper).

I am interested in working on this issue. If you think we should add this, then please assign the issue to me and I can raise PR.

cc @bhack

ashutosh1919 avatar Jun 29 '22 03:06 ashutosh1919

As the focal loss Is going to be duplicated in Keras-cv can you open a ticket in keras-cv so that if they are interested we avoid another potential duplication?

bhack avatar Jun 29 '22 10:06 bhack

Created #16735

ashutosh1919 avatar Jun 30 '22 00:06 ashutosh1919

TensorFlow Addons is transitioning to a minimal maintenance and release mode. New features will not be added to this repository. For more information, please see our public messaging on this decision: TensorFlow Addons Wind Down

Please consider sending feature requests / contributions to other repositories in the TF community with a similar charters to TFA: Keras Keras-CV Keras-NLP

seanpmorgan avatar Mar 01 '23 04:03 seanpmorgan