Chapter 09.02: Problem Definition
Hyperparameter tuning is the process of finding good model hyperparameters. In this section we formalize the problem of tuning and explain why tuning is computationally hard.
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## Which statements are true?
- [x] Tuning means optimizing hyperparameters.
- [x] Doing tuning well is hard; nested resampling can help.
- [x] Good tuning is crucial to achieving good performance for most ML algorithms.
- [ ] Tuning optimizes the inner loss.