Clustering Tools
Browse all available clustering tools.
Available tools
- Affinity Propagation Clustering Tool Cluster numeric points by exchanging responsibility and availability messages between candidate exemplars.
- BIRCH Microclustering Demonstrator Build order-dependent BIRCH-style microclusters using a maximum-radius threshold.
- Fuzzy C-Means Clustering Tool Fit fuzzy c-means memberships that sum to one across clusters for each point; fuzzifier must exceed one.
- K-Means Clustering Tool Cluster numeric points by iterative nearest-centroid assignment and arithmetic centroid updates. Farthest-point deterministic initialization avoids random results.
- K-Means++ Initializer Choose reproducible initial centroids with k-means++ distance-weighted sampling.
- Mean Shift Clustering Tool Shift each point to the mean of points within a fixed Euclidean bandwidth, then merge nearby modes. Bandwidth controls the number of modes.
- OPTICS Clustering Tool Order multidimensional points by density reachability with the OPTICS clustering algorithm.
- Possibilistic C-Means Clustering Tool Fit possibilistic typicalities independently for each cluster using a caller-supplied squared-distance scale; unlike fuzzy memberships, rows need not sum to one.