MATLAB Deep Learning by Phil Kim

Author:Phil Kim
Language: eng
Format: epub
Publisher: Apress, Berkeley, CA

The primary difference of the cross entropy function from the quadratic function of Equation 3.9 is its geometric increase. In other words, the cross entropy function is much more sensitive to the error. For this reason, the learning rules derived from the cross entropy function are generally known to yield better performance. It is recommended that you use the cross entropy-driven learning rules except for inevitable cases such as the regression.

We had a long introduction to the cost function because the selection of the cost function affects the learning rule, i.e., the formula of the back-propagation algorithm. Specifically, the calculation of the delta at the output node changes slightly. The following steps detail the procedure in training the neural network with the sigmoid activation function at the output node using the cross entropy-driven back-propagation algorithm . 1.Initialize the neural network’s weights with adequate values.

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