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.

Views

This node has no views

Workflows

Developers

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.

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

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!