Why is Regularization Important in Nanotechnology?
In the field of nanotechnology, the datasets are often highly complex and multidimensional. This complexity can lead to models that fit the training data too closely, thus failing to perform well on new, unseen data. Regularization helps in maintaining a balance between fitting the data well and keeping the model simple. This is especially important when modeling phenomena at the nanoscale, where the margin for error is extremely small.
