Machine Learning for OpenCV 4 - Second Edition

Combining grid search with nested cross-validation

Although grid search with cross-validation makes for a much more robust model selection procedure, you might have noticed that we performed the split into training and validation sets still only once. As a result, our results might still depend too much on the exact training-validation split of the data.

Instead of splitting the data into training and validation sets once, we can go a step further and use multiple splits for cross-validation. This will result in what is known as nested cross-validation, and the process is illustrated in the following diagram:

In nested cross-validation, there ...