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# General Considerations

Before we consider concrete classes of supervised learning methods, we have a look at basic principles common to (almost) all methods.

- Problem and Workflow
- Introductory Example (k-NN)
- Quality Measures
- Scaling
- Feature Reduction
- Hyperparameter Tuning

Related projects:

- Forged Banknotes

  - Detecting Forgery with k-NN

  - Quality Measures

  - Hyperparameter Optimization

- QMNIST Feature Reduction