KNIME WEKA nodes (3.7) version 4.1.0.v201911281246 by KNIME AG, Zurich, Switzerland
Class for constructing a random forest*. For more information see: Leo Breiman (2001)
Random Forests. Machine Learning. 45(1):5-32.
(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.
(*) RANDOM FORESTS is a registered trademark of Minitab, LLC and is used with Minitab's permission.
I: Number of trees to build.
K: Number of features to consider (<1=int(logM+1)).
S: Seed for random number generator. (default 1)
depth: The maximum depth of the trees, 0 for unlimited. (default 0)
print: Print the individual trees in the output
num-slots: Number of execution slots. (default 1 - i.e. no parallelism)
D: If set, classifier is run in debug mode and may output additional info to the console
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, Date 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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