NodeDL4J Feedforward Learner (Classification)


This node performs supervised training of a feedforward deep learning model for classification. Thereby, the learning procedure can be adjusted using several training methods and parameters, which can be customized in the node dialog. Additionally, the node supplies further methods for regularization, gradient normalization and learning refinements. The learner node automatically adds an output layer to the network configuration, which can be also configured in the node dialog. For classification, the output layer will always use 'softmax' as the activation function and the number of outputs will be automatically set to match the number of unique labels used for training. The output of the node is a trained deep learning model which can be used to predict the labels of unseen data instances.

Input ports

  1. Deep Learning Model Type: DL4J Model
    Finished configuration of a deep learning network.
  2. Data Table Type: Data
    Data table containing training data.

Output ports

  1. Deep Learning Model Type: DL4J Model
    Trained Deep Learning Model