Hands-On Unsupervised Learning with Python
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Clustering Fundamentals

In this chapter, we are going to introduce the fundamental concept of cluster analysis, focusing the attention on our main principles that are shared by many algorithms and the most important techniques that can be employed to evaluate the performance of a method.

In particular, we are going to discuss:

  • An introduction to clustering and distance functions
  • K-means and K-means++
  • Evaluation metrics
  • K-Nearest Neighbors (KNN)
  • Vector Quantization (VQ)