Which function do I need? | A first example: k-means | Scoring a partition from elsewhere | Letting a clustering function do the work | Soft and model-based clustering | Choosing the number of clusters | Where next | Session information | References

Classical and simplified widths | Three properties of the simplified widths | Where the cluster labels come from | Ranges of the widths | Which comparisons are valid | Session information | References

Widths from membership probabilities | Fuzzy c-means: soft and distance-based widths coincide | Averaging and the exponent a | Comparing soft clustering algorithms | Choosing the number of clusters | Pitfalls | Session information | References

Data with a block structure | Silhouettes for a double k-means fit | Choosing the numbers of row and column clusters | Soft block clustering | Session information | References