How can I balance trade-offs between bias reduction and model accuracy

Question

With the help of code snippets and proper examples can you tell me How can I balance trade-offs between bias reduction and model accuracy?

Answer 1

To balance bias reduction and model accuracy, you can use regularization and adversarial training and carefully control the debiasing strength.

Here is the code snippet you can refer to:

In the above code, we are using the following key points:

• Adversarial regularization can be used to penalize biased outputs without significantly affecting performance.
• Early stopping during training can prevent the model from overfitting to bias patterns at the cost of accuracy.

Hence, by referring to the above, you can balance the trade-offs between bias reduction and model accuracy.