KNIME Ensemble Learning version 4.0.0.v201906060925 by KNIME AG, Zurich, Switzerland
Together with the corresponding loop end node a boosting loop can be constructed. It repeatedly trains simple models and weights them according to their classification error. The algorithm used is AdaBoost.SAMME, i.e. is can also cope with multi-class problems. The first output contains the re- and over-sampled dataset, rows that have been predicted wrong are contained more often than correctly predicted rows.
To use this node in KNIME, install KNIME Ensemble Learning from the following update site:
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