Keras Softmax Layer

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.

Options

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.
Axis: 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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Installation

To use this node in KNIME, install the extension KNIME Deep Learning - Keras Integration from the below update site following our NodePit Product and Node Installation Guide:

v5.3

A zipped version of the software site can be downloaded here.

Plugin provider: KNIME AG, Zurich, Switzerland

Plugin version: 5.3.0.v202312081534

On NodePit since: 2024-07-09

Last update: 2024-11-21

KNIME versions: Since v3.6

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