Softmax activation function

Softmax activation function

The softmax activation function is a neural transfer function. In neural networks, transfer functions calculate a layer's output from its net input. It is represented as:

p_i = frac{exp(q_i)}{Sigma_{j=1}^nexp(q_j)}

Where "p" is the value of an output node, "q" is the net input to an output node, and "n" is the number of output nodes.


Wikimedia Foundation. 2010.

Игры ⚽ Поможем написать курсовую

Look at other dictionaries:

  • Artificial neural network — An artificial neural network (ANN), usually called neural network (NN), is a mathematical model or computational model that is inspired by the structure and/or functional aspects of biological neural networks. A neural network consists of an… …   Wikipedia

  • Backpropagation — Backpropagation, or propagation of error, is a common method of teaching artificial neural networks how to perform a given task. It was first described by Paul Werbos in 1974, but it wasn t until 1986, through the work of David E. Rumelhart,… …   Wikipedia

Share the article and excerpts

Direct link
Do a right-click on the link above
and select “Copy Link”