Auto Clustering
The Auto Clustering algorithm is a highly configurable and scalable clustering engine
that uses the Gower distance metric for handling numerical, categorical, or mixed inputs
automatically to determine the optimal number of clusters.
Specify a minimal configuration, designate inputs as optional, and let the engine work out the rest. Or, tell the engine to specifically implement a method for a tailored clustering approach. For large datasets, the engine utilizes an automatic sampling approach to avoid bias.
Developed for Infor's Augmented Intelligence (AI) suite, Auto Clustering is designed to provide a valuable solution through a combination of K-means, K-modes, and K-prototypes automatically based on the features.
Note: A new version of this algorithm is available. (The new version is
the default.) You can choose the version from the configuration panel using the Algorithm Version list. We recommend using the latest
available version to benefit from the most up-to-date improvements and achieve the best
possible performance.