Spark k-Means

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.

Input ports

1. Type: Spark Data
   JavaRDD
   Input data (JavaRDD)

Output ports

1. Type: Spark Data
   Labeled input
   The input data labeled with the cluster they are contained in.
2. Type: Spark MLlib Model
   MLlib Cluster Model
   MLlib Cluster Model