Neural Network v0.1.2 NeuralNetwork.Neuron
A neuron makes up a network. It’s purpose is to sum its inputs and compute an output. During training the neurons adjust weights of its outgoing connections to other neurons.
Summary
Functions
Activate a neuron. Set the input value and compute the output Input neuron: output will always equal their input value Bias neuron: output is always 1. Other neurons: will squash their input value to compute output
Sigmoid function. See more at: https://en.wikipedia.org/wiki/Sigmoid_function
Connect two neurons
Lookup and return a neuron
Create a neuron agent
Backprop using the delta. Set the neuron’s delta value
Pass in the pid, and a map to update values of a neuron
iex> {:ok, pid} = NeuralNetwork.Neuron.start_link
...> NeuralNetwork.Neuron.update(pid, %{input: 3, output: 2, incoming: [1], outgoing: [2], bias?: true, delta: 1})
...> neuron = NeuralNetwork.Neuron.get(pid)
...> neuron.output
2
Functions
Activate a neuron. Set the input value and compute the output Input neuron: output will always equal their input value Bias neuron: output is always 1. Other neurons: will squash their input value to compute output
Sigmoid function. See more at: https://en.wikipedia.org/wiki/Sigmoid_function
Example
iex> NeuralNetwork.Neuron.activation_function(1)
0.7310585786300049