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.
Implementation of the RProp algorithm for multilayer feedforward networks.
RPROP performs a local adaptation of the weight-updates according to the
behavior of the error function.
For further details see: Riedmiller, M. Braun, H. : "A direct adaptive method for faster
backpropagation learning: theRPROP algorithm",Proceedings of the IEEE
International Conference on Neural Networks (ICNN) (Vol. 16, pp. 586-591).
Piscataway, NJ: IEEE.
This node provides a view of the error plot.
If the optional PMML inport is connected and contains
preprocessing operations in the TransformationDictionary those are
added to the learned model.
0 | Datatable with training data |
1 | Optional PMML port object containing preprocessing operations. |
0 | RProp trained Neural Network |