DeprecatedDecisions Tree Ensembles for KNIME version 4.2.0.v201912131002 by KNIME AG, Zurich, Switzerland
Learns a random forest* (an ensemble of decision trees) for regression. Each of the regression tree models is learned on a different set of rows (records) and/or a different set of columns (describing attributes), whereby the latter can also be a bit-vector or byte-vector descriptor (e.g. molecular fingerprint). The output model describes an ensemble of regression tree models and is applied in the corresponding predictor node using a simply mean of the individual predictions.
For a more general description and suggested default parameters see the node description of the classification Random Forest Learner node.
This node provides a subset of the functionality of the Tree Ensemble Learner (Regression). If you need additional functionality, please check out the Tree Ensemble Learner (Regression)
Select the attributes to use learn the model. Two variants are possible.
Fingerprint attribute uses the different bit/byte positions in the selected bit/byte vector as learning attributes (for instance a bit vector of length 1024 is expanded to 1024 binary attributes or 1024 long byte vector is expanded to the corresponding number of numeric attributes). All vectors in the selected column must have the same length.
Column attributes are nominal and numeric columns used as descriptors. Numeric columns are split in a <= fashion; nominal columns are currently split by creating child nodes for each of the values.
To use this node in KNIME, install KNIME Ensemble Learning Wrappers 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 firstname.lastname@example.org, 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.