This node maps data of a high dimensional space onto a lower (usually 2 or 3) dimensional space with respect to a set of fixed data points. Therefore modified Sammons mapping is applied, which iteratively decreases the difference of the distances of high and low dimensional data. When adjusting the position of a low dimensional data point by default not its neighbors (or all other data points) are taken into account but a specified set of fixed data points which are not modified. Additionally all the other data points (and not only the fixed points) can be taken into account when adjusting its positions, therefore the setting "Project only" has to be unchecked. If the setting is checked the data points will be mapped only with respect to the fixed data. The distances of the data points to project in high dimensional space as well as the distances of the fixed data (to the data to project) must be provided by distance matrix columns.

- Number of rows to use
- Specifies the number of rows to apply the MDS on.
- Project only
- If checked the input data is mapped only with respect to the specified fixed data points (see tab 'Fixed data'). If unchecked, the other (not fixed) data points are taken into account too, when adjusting the position of each single data point.
- Epochs
- Specifies the number of epochs to train.
- Learn rate
- Specifies the learning rate to use. The learning rate is decreased automatically over the trained epochs.
- Random seed
- Specifies the random seed to use, which allows to reproduce a mapping even if the initialization is done randomly.
- Output dimension
- Specifies the dimension of the mapped output data.
- Distance matrix column of data to project
- The column (of data table at port 1) containing the distances of the data points to project (to itself and the data points to project).
- MDS columns
- Specifies the columns to use as fixed (mds column) data. Be aware that the chosen columns represent the lower dimensional data which is used to project the input data to. The number of columns to choose has to be equal to the output dimension.
- Distance matrix column of fixed data
- The column (of data table at port 0) containing the distances of the fixed data points (to itself and the data points to project).

- This node has no views

- No workflows found

- No links available

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:

v5.3

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**.

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.**