1.1 - 8.10 - Cluster Analysis - Teradata Vantage

Teradata Vantage™ - Machine Learning Engine Analytic Function Reference

Teradata Vantage
Release Number
October 2019
Content Type
Programming Reference
Publication ID
English (United States)
Function Description
Canopy (ML Engine) Simple, fast, accurate function for grouping objects into preliminary clusters. Often used as an initial step in more rigorous clustering techniques, such as k-means.
MinHash (ML Engine) Probabilistic clustering method that assigns a pair of users to the same cluster with probability proportional to the overlap between the sets of items that these users have bought.
Modularity (ML Engine) Discovers communities (clusters) in input graphs without advance information about the clusters. Detects communities by discovering the strength of relationships among data points.
Gaussian Mixture Model Functions (ML Engine) Fit a Gaussian mixture model (GMM) to input data, using either a basic GMM algorithm with a fixed number of clusters or a Dirichlet Process GMM (DP-GMM) algorithm with a variable number of clusters.
KMeans Functions (ML Engine) Create and use model that is table of cluster centroids. Optionally output clusters themselves.
KModes Functions (ML Engine) Extends KMeans functions to support categorical data.