This node maps data of a high dimensional space onto a lower (usually 2 or 3) dimensional space. Therefore the Sammons mapping is applied, which iteratively decreases the difference of the distances of high and low dimensional data. Each original data point is represented by a data point of a lower dimension. The Sammons mapping tries to keep the distance information of the high dimensional data by adjusting the low dimensional data points in a certain way. Each low dimensional data point is moved around a bit towards or back from the other points according to its high dimensional distances. This procedure is repeated a specified number of epochs or iterations respectively. The distances in the original high dimensional space have to be provided by a column containing distance vectors (see distance matrix calculate node). According to these distances the data is mapped onto the lower dimensional space. In the low dimensional space the Euclidean distance is used to arrange the points.
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.
To use this node in KNIME, install the extension KNIME Distance Matrix from the below update site following our NodePit Product and Node Installation Guide:
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 mail@nodepit.com, follow @NodePit on Twitter or botsin.space/@nodepit on Mastodon.
Please note that this is only about NodePit. We do not provide general support for KNIME — please use the KNIME forums instead.