- Code for General Use Written for this Chapter
- BSAS.m (the Basic Sequential Algorithmic Scheme)

- MBSAS.m (the Modified Basic Sequential Algorithmic Scheme)

- findClosestCluster.m (finds the cluster closet to a given point)

- getClusterRepresentative.m (returns the point representation of a cluster)

- estimateNumberOfClusters.m (Estimates the number of clusters on a given data set using BSAS)

- TTSAS.m (the Two-Threshold Sequential Scheme)

- merging.m (implements Fu's simple cluster merging procedure)

- merging_example.m (demonstrates the simple cluster merging procedure)

- BSAS.m (the Basic Sequential Algorithmic Scheme)
- Verifications/Duplication of Figures or Results from the Text
- dup_figure_12_1.m (uses BSAS to duplicate figure 12.1)

- dup_figure_12_2.m (estimate the number of clusters like in figure 12.2)

- dup_figure_12_3.m (runs TTSAS and MBSAS on data like in figure 12.3)

- dup_figure_12_1.m (uses BSAS to duplicate figure 12.1)
- Problem Solutions
- chap_12_prob_3.m (runs BSAS and MBSAS on the given data set)

- plot_labeled.m (plotting routine)

- plot_labeled.m (plotting routine)

- chap_12_prob_3.m (runs BSAS and MBSAS on the given data set)

- Matlab implementations of some sequential clustering algorithms similar to the ones discussed here

John Weatherwax