How do I understand that I am getting the correct output when using the sigmoid function in a neural network? Considering that a sigmoid function (activation function) helps with checking the value between 0.00001 to 1.Also, what does it mean if you get output that are around 0.999877 or 0.999955 or within those values? Do these values represent how accurate the neural net is? Perceptron→ outputx3First of all, what is a Perceptron ? A Perceptron is a type of artificial neuron which takesin several binary inputs x1, x2, ..., xn and produces a single binary output. In theexample shown above, there are three inputs x1, x2 and x3.In order to compute an output, here's what you could do (O = Output):a) Sum up the inputs. O = x1 + x2 + x3b) Apply a linear mathematical operation to the inputs. O = (x1 * x2) + x3x1X2

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Computer Networking: A Top-Down Approach (7th Edition)

7th Edition

ISBN:9780133594140

Author:James Kurose, Keith Ross

Publisher:James Kurose, Keith Ross

Chapter1: Computer Networks And The Internet

Section: Chapter Questions

Problem R1RQ: What is the difference between a host and an end system? List several different types of end...

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How do I understand that I am getting the correct output when using the sigmoid function in a neural network? Considering that a sigmoid function (activation function) helps with checking the value between 0.00001 to 1.

Also, what does it mean if you get output that are around 0.999877 or 0.999955 or within those values? Do these values represent how accurate the neural net is?