How can data-centric AI techniques optimize Generative AI for imbalanced data

Question

Can you tell me how data-centric AI techniques can optimize Generative AI for imbalanced data?

Answer 1

Data-centric AI techniques improve Generative AI by enhancing dataset quality through augmentation, resampling, and synthetic data generation, ensuring balanced training.

Here is the code snippet you can refer to:

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

• Data Augmentation: Uses SMOTE or GANs to generate more representative samples.
• Balancing Class Distribution: Prevents model bias toward majority classes.
• Synthetic Data Generation: Creates realistic but artificial samples to enhance learning.
• Improved Model Generalization: Reduces overfitting to dominant patterns.

Hence, by referring to above you can optimize Generative AI for imbalanced data.