Module Learning Outcomes

Module Learning Outcomes

By the end of the module, students are expected to:

  • Explain the notion of similarity-based algorithms.
  • Broadly describe how π‘˜-NNs use distances.
  • Describe the effect of using a small/large value of the hyperparameter π‘˜ when using the π‘˜-NN algorithm.
  • Explain the problem of curse of dimensionality.
  • Explain the general idea of SVMs with RBF kernel.
  • Compare and contrast π‘˜-NNs and SVM RBFs.
  • Broadly describe the relation of gamma and C hyperparameters with the fundamental tradeoff.

Let’s start!