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DL4J Feedforward Learner (Pretraining) (legacy)

KNIME LabsDeep LearningDL4J (legacy)LearnUnsupervised
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This node performs unsupervised pretraining of a feedforward deep learning model. 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 pretraining the network architecture needs to contain layers which are can be trained unsupervised. Such layers are for example an RBM or a Autoencoder. Usually, this node is used together with a classification learner node which performs finetuning of the output layer after the network was pretrained. The output of the node is a pretrained deep learning model.

The KNIME Deeplearning4J Integration has been marked as legacy with KNIME Analytics Platform 5.0 and will be deprecated in a future version. If you are using this extension in a production workflow, consider switching to one of the other deep learning integrations available in KNIME Analytics Platform.

Node details

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

Extension

The DL4J Feedforward Learner (Pretraining) (legacy) node is part of this extension:

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Related workflows & nodes

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