Interactive Clustering (Two-step clustering)

Interactive clustering is based on a two-step clustering algorithm. This two-staged algorithm first agglomerates data points into small clusters using K-Means clustering. Then, it applies agglomerative hierarchical clustering in order to further cluster the data, while also building a hierarchy between the smaller clusters, which can then be interpreted. It therefore allows to extract hierarchical information from datasets larger than a few hundred lines, which cannot be achieved through standard methods.
The clustering can then be manually adjusted in DSS's interface.