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 2.4.0 and later versions are supported.
This component is not shipped with your Talend Studio by default. You need to install it using the Feature Manager. For more information, see Installing features using the Feature Manager.
For more technologies supported by Talend, see Talend components.