The following node is available in the Open Source KNIME predictive analytics and data mining platform version 2.7.1. Discover over 1000 other nodes, as well as enterprise functionality at http://knime.com.
Together with the corresponding loop start node a boosting loop can be constructed. It repeatedly trains simple models and weighs them according to their classification error. The algorithm used is AdaBoost.SAMME, i.e. is can also cope with multi-class problems. The loop is stopped either after the maximum number of iterations has been reached or the weight for a model is only slightly above 0 (meaning the prediction error is too big).
0 | The trained model |
1 | The data with predicted classes and also the real class values |
0 | The boosted models together with their weights in data table |