Nanotechnology often involves dealing with high-dimensional data and complex models. Regularization techniques like l1 and l2 can help in: - Preventing Overfitting: Ensuring that the models generalize well to new data. - Feature Selection: Identifying the most important features affecting the outcomes. - Improving Model Interpretability: Making it easier to understand which variables are most impactful. - Enhancing Predictive Accuracy: Leading to more reliable and robust predictions.
