Full softmax: Revision history

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20 March 2023

  • curprev 01:1801:18, 20 March 2023‎ Walle talk contribs‎ 4,035 bytes +4,035‎ Created page with "{{see also|Machine learning terms}} ==Introduction== In machine learning, the softmax function is an essential component for the classification of multiple categories. The full softmax, also known as the standard softmax, is a method used to convert a vector of real numbers into a probability distribution. The output of the full softmax function is a probability distribution that can be interpreted as the likelihood of an input belonging to each of the considered classes..."
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