KNIME Neighborgrams & Parallel Universe Nodes version 4.2.0.v202002240952 by KNIME AG, Zurich, Switzerland
This node is used to construct and view Neighborgrams created from the data input. It does not allow for an interactive clustering (there are more specific nodes, which enable manual or automatic clustering).
The general idea of the Neighborgram data structure is the following: For a selected set of (labeled) objects, construct a neighborhood histogram (called Neighborgram, i.e. a single cell in the node's table view). An indivdual neighborgram summarizes the close vicinity of the respective object according to the selected distance or similarity measure. It usually shows a few hundreds of the closest neighbors (though a different neighbor count can be specified in the dialog), which are colored according their class label (the class coloring needs to be done using a Color Manager node, e.g.). Using the view, the user can select individual neighbors or entire neighborhoods and use other KNIME views to get more details on the selected objects. There are also basic clustering schemes available in the view, which allow the user to navigate between individual neighborgrams and their derived cluster candiates.
The view also supports different "universes", i.e. different measures of similarity. In order to enable this feature, the user needs to use universe marker node beforehand and assign individual columns to universes.
Details on the algorithm have been published in
Michael R. Berthold, Bernd Wiswedel, David E. Patterson
Interactive Exploration of Fuzzy Clusters Using Neighborgrams,
Fuzzy Sets and Systems, vol. 149, no. 1, pp. 21-37, Elsevier, 2005
To use this node in KNIME, install KNIME Neighborgram & ParUni from the following update site:
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.
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.