simCluster is simMachines’ predictive clustering algorithm - it generates and presents groups of like objects in data based on a prediction objective. simCluster identifies the similarities and differences between group members based on their class. simCluster is also capable of running unsupervised clustering. In addition to classifying, simCluster’s clustering capacities allow for insightful visualizations of data groups to be easily created.
simCluster+ is simMachines’ metric learning clustering algorithm. Like simCluster, it identifies clusters of objects that have similar attributes and, if used in supervised mode, identifies clusters of objects by their most class-predictive attributes.
simCluster+ uses metric learning and a technique that can create K-Means clustering or K-Spilling clusters, unlike simCluster which uses agglomerative clusters.