Selecting the optimal regularization parameter is critical for model performance. Techniques such as cross-validation are often employed to determine the best parameter value. In nanotechnology, where experimental data can be costly and difficult to obtain, it is important to use these techniques to ensure that models are both accurate and reliable.
