Mechatronic Systems Integration
Leave-one-out cross-validation (LOOCV) is a model validation technique where a single observation from the dataset is used as the validation set, while the remaining observations form the training set. This process is repeated for each observation in the dataset, allowing for a comprehensive assessment of the model's performance. LOOCV is particularly useful in scenarios where the dataset is small, as it maximizes the amount of training data used for each model training iteration.
congrats on reading the definition of leave-one-out cross-validation. now let's actually learn it.