The following node is available in the Open Source KNIME predictive analytics and data mining platform version 2.7.1. Discover over 1000 other nodes, as well as enterprise functionality at http://knime.com.
This node 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 algorithm terminates when the
cluster assignments do not change anymore.
The clustering algorithm uses the Euclidean distance on the selected
attributes. The data is not normalized by the node (if required,
you should consider to use the "Normalizer" as a preprocessing step).
If the optional PMML inport is connected and contains
preprocessing operations in the TransformationDictionary those are
added to the learned model.
The node can be configured as follows:
0 | Input to clustering. All numerical values and only these are considered for clustering. |
1 | Optional PMML port object containing preprocessing operations. |
0 | The input data labeled with the cluster they are contained in. |
1 | PMML cluster model |