Why is k-fold Cross Validation Important in Nanotechnology?
In Nanotechnology, datasets can be small and highly variable due to the complexity and specificity of nanoscale phenomena. Traditional train-test splits might not suffice, as they can lead to overfitting or underfitting. k-fold cross validation addresses these issues by ensuring that every data point is used for both training and testing, leading to a more accurate and generalizable model. This is crucial for applications like nanomaterial characterization, drug delivery systems, and nanoelectronics, where precise predictions are essential.
