How can you perform cross-validation in PyBrain?
Performing cross-validation in PyBrain involves splitting the dataset into multiple folds, training the model on a subset of folds, and evaluating its performance on the remaining fold. This process is repeated multiple times, with each fold serving as both a training and validation set. PyBrain does not have built-in support for cross-validation, but you can implement it using techniques available in other libraries such as scikit-learn.
