RProp MLP Learner (deprecated)

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.

Input ports

1. Type: Table
   Training Data
   Datatable with training data
2. Type: PMML
   PMML Preprocessing
   Optional PMML port object containing preprocessing operations.

Output ports

1. Type: PMML
   Neural Network
   RProp trained Neural Network