KNIME WEKA nodes (3.7) version 4.2.0.v202007031307 by KNIME AG, Zurich, Switzerland
This class is an implementation of the Ordinal Learning Method (OLM). Further information regarding the algorithm and variants can be found in: Arie Ben-David (1992)
Automatic Generation of Symbolic Multiattribute Ordinal Knowledge-Based DSSs: methodology and Applications.Decision Sciences.
(based on WEKA 3.7)
For further options, click the 'More' - button in the dialog.
All weka dialogs have a panel where you can specify classifier-specific parameters.
R: The resolution mode. Valid values are: 0 for conservative resolution, 1 for random resolution, 2 for average, and 3 for no resolution. (default 0).
C: The classification mode. Valid values are: 0 for conservative classification, 1 for nearest neighbour classification. (default 0).
U: SSet maximum size of rule base (default: -U <number of examples>)
The Preliminary Attribute Check tests the underlying classifier against the DataTable specification at the inport of the node. Columns that are compatible with the classifier are marked with a green 'ok'. Columns which are potentially not compatible are assigned a red error message.
Important: If a column is marked as 'incompatible', it does not necessarily mean that the classifier cannot be executed! Sometimes, the error message 'Cannot handle String class' simply means that no nominal values are available (yet). This may change during execution of the predecessor nodes.
Capabilities: [Nominal attributes, Binary attributes, Unary attributes, Empty nominal attributes, Numeric attributes, Missing values, Nominal class, Binary class, Missing class values] Dependencies:  min # Instance: 1
It shows the command line options according to the current classifier configuration and mainly serves to support the node's configuration via flow variables.
To use this node in KNIME, install KNIME Weka Data Mining Integration (3.7) from the following update site:
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