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Class-Balanced Loss Based on Effective Number of Samples #2732

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ashutosh1919 opened this issue Jun 29, 2022 · 3 comments
Closed

Class-Balanced Loss Based on Effective Number of Samples #2732

ashutosh1919 opened this issue Jun 29, 2022 · 3 comments

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@ashutosh1919
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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

@bhack
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bhack commented Jun 29, 2022

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?

@ashutosh1919
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Created #16735

@seanpmorgan
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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

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