What is model complexity in AI?

What is model complexity in AI?

Model complexity in AI refers to the capacity of a model to capture patterns in data. It can affect performance.

How does it impact overfitting and underfitting?

Higher model complexity can lead to overfitting, where the model learns noise instead of the underlying pattern. Conversely, a simpler model might underfit.

What are some ways to manage model complexity?

You can manage model complexity through techniques like regularization, pruning, and selecting appropriate model architectures.

Can you give examples of regularization techniques?

Sure! Common regularization techniques include L1 and L2 regularization, dropout, and early stopping.