Why is data balance important in AI training?

Why is data balance important in AI training?

Data balance ensures that the AI model learns from a diverse set of examples, reducing bias and improving accuracy.

What happens if the data is imbalanced?

Imbalanced data can lead to biased models that perform poorly on underrepresented classes, affecting overall performance.

How can I achieve data balance in my dataset?

You can achieve data balance by techniques like oversampling, undersampling, or using synthetic data generation methods.

Are there tools to help with data balancing?

Yes, there are several tools like SMOTE, ADASYN, and various libraries in Python that can assist with data balancing.