Chapter 3
Supervised Learning
Section 6
Model Selection
There are two main problems—how do we evaluate and how well will our supervised learning model generalize to new data? And also, how do we choose the optimal model parameters to do this? - Explain what overfitting is and how it can create poor model generalization - Explain how regularization can help solve the overfitting problem - Explain how cross-validation is used to select the optimal regularization parameter. Also show a demonstration of this in Scala.