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Hierarchical Clustering

Schrödinger extension for KNIME Workbench version by Schrödinger

Hierarchical Clustering based on a pairwise distance matrix.

Available linkage types:

  • single
  • complete
  • average
  • centroid
  • mcquitty
  • ward
  • weightedcentroid
  • flexiblebeta
  • schrodinger

Backend implementation

canvasHC is used to implement this node.


Number of clusters
Create set of clusters using the specified value.
Use Kelley criterion
Create set of clusters based on the minimum in the Kelley cost function.
Merging distance
Create set of clusters at or below the specified distance value.

Input Ports

Pairwise distance matrix in Binary format

Output Ports

Clustering results


Standard output of Hierarchical Clustering
Standard output of Hierarchical Clustering

Best Friends (Incoming)

Best Friends (Outgoing)



To use this node in KNIME, install Schrödinger Extensions for KNIME from the following update site:


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