A mathematical analysis of the effects of lasso penalty and its effects on linear regression, including possible extensions to deep learning — Introduction Curve fitting — under and over fitting As discussed in my previous article, issues with ‘curve fitting’ occur when the problem is ill-posed. Underfitting is usually not a big problem because we have the option to expand the feature set by acquiring/engineering new features. However, overfitting is not easy to handle.