4 Optimizing the training process: Underfitting, overfitting, testing, and regularization
In this chapter
- what is underfitting and overfitting
- some solutions for avoiding overfitting: testing, the model complexity graph, and regularization
- calculating the complexity of the model using the L1 and L2 norms
- picking the best model in terms of performance and complexity
This chapter is different from most of the chapters in this book, because it doesn’t contain a particular machine learning algorithm. Instead, it describes some potential problems that machine learning models may face and effective practical ways to solve them.
Imagine that you have ...
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