KNIME Deeplearning4J Integration version 4.2.0.v202007031306 by KNIME AG, Zurich, Switzerland
This node performs supervised training of a feedforward deep learning model for regression. 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 regression, the output layer will always use 'identity' as the activation function and the number of outputs will be automatically set to match the number target values. The output of the node is a trained deep learning model which can be used to predict target values.
To use this node in KNIME, install KNIME Deeplearning4J Integration (64bit only) from the following update site:
You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.
Do you have feedback, questions, comments about NodePit, want to support this platform, or want your own nodes or workflows listed here as well? Do you think, the search results could be improved or something is missing? Then please get in touch! Alternatively, you can send us an email to email@example.com, follow @NodePit on Twitter, or chat on Gitter!
Please note that this is only about NodePit. We do not provide general support for KNIME — please use the KNIME forums instead.