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Keras Softmax Layer

KNIME Deep Learning - Keras Integration version 4.3.0.v202012011122 by KNIME AG, Zurich, Switzerland

The softmax function is commonly used as the last layer in a classification network. It transforms an unconstrained n-dimensional vector into a valid probability distribution. Note that the input to a softmax must have at least one dimension in addition to the batch dimension. Corresponds to the Keras Softmax Layer.


Name prefix
The name prefix of the layer. The prefix is complemented by an index suffix to obtain a unique layer name. If this option is unchecked, the name prefix is derived from the layer type.
The axis along which to apply the softmax normalization. Python-style negative indexing is supported i.e. -1 corresponds to the last axis, -2 to the second last and so on. Axis 0 corresponds to the batch axis.

Input Ports

The Keras deep learning network to which to add a Softmax layer.

Output Ports

The Keras deep learning network with an added Softmax layer.

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