Data clustering (or cluster analysis) is a method of dividing the data points into several groups called clusters. All data points within a cluster are mutually similar as compared to data points belonging to different clusters. Thus, clusters are groups segregated based on identical traits.
Clustering can be hard or soft. In hard clustering, a data point either belongs to a cluster completely or not. In soft clustering, the probability of a data point belonging to a cluster is determined.
In rubiscape, the Clustering algorithms are,

• Centroid Based Clustering
• Connectivity Based Clustering
• Density Based Clustering
• Incremental Learning

In the task pane, click Textual analysis, and then click Clustering.

For more information, refer to Clustering.