This is a Monte Carlo simulation technique used for model validation, where data is split into training and testing sets multiple times and the results are averaged to estimate how well the model generalizes to new data.
This is a Monte Carlo simulation technique used for model validation, where data is split into training and testing sets multiple times and the results are averaged to estimate how well the model generalizes to new data.