0 ×

Hierarchical Clustering

Schrödinger extension for KNIME Workbench version 20.4.144.202011111133 by Schrödinger

Hierarchical Clustering based on a pairwise distance matrix.

Available linkage types:

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

Backend implementation

utilities/canvasHC
canvasHC is used to implement this node.

Options

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

Icon
Pairwise distance matrix in Binary format

Output Ports

Icon
Clustering results

Views

Standard output of Hierarchical Clustering
Standard output of Hierarchical Clustering

Best Friends (Incoming)

Best Friends (Outgoing)

Workflows

Installation

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

KNIME 4.2

You don't know what to do with this link? Read our NodePit Product and Node Installation Guide that explains you in detail how to install nodes to your KNIME Analytics Platform.

Wait a sec! You want to explore and install nodes even faster? We highly recommend our NodePit for KNIME extension for your KNIME Analytics Platform. Browse NodePit from within KNIME, install nodes with just one click and share your workflows with NodePit Space.

Developers

You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.