How do I validate an AI model?

How do I validate an AI model?

Validating an AI model involves testing its performance on unseen data to ensure it generalizes well. Would you like to know more about specific validation techniques?

Yes, what are some common validation techniques?

Common techniques include cross-validation, holdout validation, and k-fold validation. Each has its own advantages depending on the dataset size and model complexity.

What is cross-validation?

Cross-validation is a technique where the dataset is divided into subsets. The model is trained on some subsets and tested on others, helping to assess its performance more reliably.

How do I implement k-fold validation?

To implement k-fold validation, you split your dataset into k subsets. Train the model k times, each time using a different subset as the test set and the remaining as the training set.