Analyzes incoming datasets in near real-time, based on applying the K-Means algorithm.
This component analyzes streaming feature vectors to continuously adapt an existing clustering model to changing circumstances. The incoming data is usually pre-processed by tModelEncoder and the K-Means model is used by tPredict to cluster given elements.
It continuously updates a K-Means clustering model out of this analysis and writes this model either in memory or in a given file system.
In local mode, Apache Spark 1.6.0 and later versions are supported.
For more technologies supported by Talend, see Talend components.