Hierarchically clusters the input data using a distance matrix.
Note: This node works only on small data sets, because it has cubic complexity.
There are two methods to do hierarchical clustering:
In order to determine the distance between clusters a measure has to be defined. Basically, there exist three methods to compare two clusters:
The distance information used by this node is either read from a distance vector column that must be available in the input data or is computed directly with usage of a connected distance measure. You can always calculate the distance matrix using the corresponding calculate node.
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.
A zipped version of the software site can be downloaded here.
Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.Try NodePit Runner!
Do you have feedback, questions, comments about NodePit, want to support this platform, or want your own nodes or workflows listed here as well? Do you think, the search results could be improved or something is missing? Then please get in touch! Alternatively, you can send us an email to email@example.com, follow @NodePit on Twitter, or chat on Gitter!
Please note that this is only about NodePit. We do not provide general support for KNIME — please use the KNIME forums instead.