How can I improve my model's generalization?

How can I improve my model's generalization?

Improving model generalization involves techniques like regularization, data augmentation, and cross-validation. What specific model are you working with?

I'm using a neural network for image classification.

For neural networks, consider using dropout layers, batch normalization, and increasing your dataset size through augmentation.

What kind of data augmentation techniques should I use?

You can use techniques like rotation, flipping, scaling, and color adjustments to enhance your dataset.

How do I implement dropout in my model?

You can implement dropout by adding a dropout layer in your model architecture, specifying the dropout rate, typically between 0.2 and 0.5.