How does data size affect overfitting in machine learning models?

How does data size affect overfitting in machine learning models?

The size of the dataset plays a crucial role in overfitting. Larger datasets generally help models generalize better.

Can you explain why larger datasets reduce overfitting?

Larger datasets provide more diverse examples, which helps the model learn the underlying patterns rather than memorizing the training data.

What happens if I have a small dataset?

With a small dataset, models are more likely to memorize the training data, leading to poor performance on unseen data.

Are there techniques to mitigate overfitting with small datasets?

Yes, techniques like data augmentation, regularization, and using simpler models can help mitigate overfitting.