What is overfitting in k-fold cross-validation?

What is overfitting in k-fold cross-validation?

Overfitting in k-fold cross-validation occurs when a model learns the noise in the training data instead of the underlying pattern.

How can I identify if my model is overfitting?

You can identify overfitting by comparing the performance metrics on training and validation sets; a large gap indicates overfitting.

What techniques can I use to prevent overfitting?

To prevent overfitting, you can use techniques like regularization, pruning, dropout, and increasing training data.

Is k-fold cross-validation effective in preventing overfitting?

Yes, k-fold cross-validation helps in assessing model performance more reliably, but it doesn't directly prevent overfitting.