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Hierarchical Clustering based on a pairwise distance matrix.
canvasHC is used to implement this node.
Available linkage types:
- single
- complete
- average
- centroid
- mcquitty
- ward
- weightedcentroid
- flexiblebeta
- schrodinger
Backend implementation
utilities/canvasHCcanvasHC is used to implement this node.
Options
Popular Predecessors
- Generate Pairwise Matrix17 %
- Hierarchical Clustering8 %
- Canvas Fingerprint Generation7 %
- RDKit From Molecule7 %
- Similarity Matrix (from Molecules)6 %
- Molecule Reader (to MAE)6 %
- Rule Engine6 %
- Smiles Reader4 %
- Sorter4 %
- SDF Reader3 %
- Hierarchical Clustering Report3 %
- Generate Pairwise Matrix (2 Inputs)3 %
- Hierarchical Cluster Assigner3 %
- Molecule Type Cast3 %
- Convert Fingerprint to Table1 %
- Molecule-to-MAE1 %
Column Rename1 %- Dissimilarity Selection (from Matrix)1 %
- SD-to-Smiles1 %
- Volume Overlap Matrix1 %
- RDKit Fingerprint1 %
- String-to-Type1 %
- Convert Table to FingerPrint1 %
- Row Filter1 %
- SDF Extractor1 %
- SDF Stripper1 %
- Distance Matrix Calculate1 %
- Fingerprints1 %
- RDKit Molecule Fragmenter1 %
Views
- Standard output of Hierarchical Clustering
- Standard output of Hierarchical Clustering
Workflows
Clustering 1-2KNIME Hub- Clustering 1-2KNIME Hub
- Clustering 1-2KNIME Hub
- Clustering 1-3KNIME Hub
- Clustering 1-3KNIME Hub
- Show all 9 workflows
Links
- No links available
Developers
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