coded
@sneezetrj0
An intriguing problem involves ensuring models don't become biased by learning from imbalanced data sources. This can lead to unfair decisions in applications and can be addressed by techniques such as data augmentation, re-sampling, or synthetic data generation to balance the classes and improve model fairness and accuracy.
0 reply
0 recast
1 reaction