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Hierarchical Clustering

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

: Pairwise distance matrix in Binary format

Output Ports

: Clustering results

Popular Predecessors

Popular Successors

Views

Standard output of Hierarchical Clustering: Standard output of Hierarchical Clustering

Workflows

Developers

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Installation

To use this node in KNIME, install the extension Schrödinger Extensions for KNIME from the below update site following our NodePit Product and Node Installation Guide:

v5.2

A zipped version of the software site can be downloaded here.

Plugin provider: Schrödinger

Plugin version: 24.3.138.v202407300410

On NodePit since: 2023-12-06

Last update: 2024-11-13

KNIME versions: v5.2, v5.1, v4.7, v4.6, v4.5, v4.4, v4.3, v4.2, v4.1, v4.0, v3.7, v3.6

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