What is leave one out cross validation?
Leave one out cross validation (LOOCV) is a technique used for model evaluation and selection. In LOOCV, each observation in the data set is individually used as a validation set, with the remaining observations forming the training set. This process is repeated for every observation, allowing for an unbiased estimation of the model's performance. LOOCV is particularly useful when working with small data sets, as it maximizes the available information for evaluation. However, LOOCV can be computationally expensive for large data sets, as it requires fitting the model multiple times. Overall, LOOCV provides a robust and reliable methodology to assess the generalizability and accuracy of a predictive model.
This mind map was published on 23 January 2024 and has been viewed 65 times.
