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

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Pairwise distance matrix in Binary format

Output Ports

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Clustering results

Views

Standard output of Hierarchical Clustering
Standard output of Hierarchical Clustering

Workflows

Links

Developers

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