This node applies the Apache Spark K-means clustering algorithm. It outputs the cluster centers for a predefined number of clusters (no dynamic number of clusters). K-means performs a crisp clustering that assigns a data vector to exactly one cluster. The data is not normalized by the node (if required, you should consider to use the "Spark Normalizer" as a preprocessing step).
Use the Spark Cluster Assigner node to apply the learned model to unseen data.
- Type: Spark Data Input data (JavaRDD)
- Type: Spark Data The input data labeled with the cluster they are contained in.
- Type: Spark MLlib Model MLlib Cluster Model