# Stability for selecting the number of clusters: literature review, questions, and ideas

Lecture slides:

- Clustering Stability — a literature review, <br>many questions, and a few ideas for answers
- Overview
- The principle of stability
- Stability as a tool for model selection in clustering
- Stabilty – the general principle
- The toy figure in favor of stability
- Generating artificial data sets
- How to use the clustering algorithm
- Distances between the clusterings
- Which clusterings to compare?
- Stability scores
- Normalization
- Selecting K, finally
- Stability in theory
- Negative results on stability
- First catch: large vs. small sample size
- Possible solution: “stability window”
- Second catch: attaining the global minimum
- Possible solution: exploring objective function
- Catch 3: What is “the right K”,<br> actually?
- The “correct K”, first approach
- The “correct” K, second approach
- Idea: hierarchy of cluster core sets
- Summary

*Author: Ulrike Von Luxburg, Max Planck Institute For Biological Cybernetics*