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