go-neural
Install
go get github.com/NOX73/go-neural
go get github.com/NOX73/go-neural/persist
go get github.com/NOX73/go-neural/learn
Neural Network
Create new network:
import "github.com/NOX73/go-neural"
//...
// Network has 9 enters and 3 layers
// ( 9 neurons, 9 neurons and 4 neurons).
// Last layer is network output.
n := neural.NewNetwork(9, []int{9,9,4})
// Randomize sypaseses weights
n.RandomizeSynapses()
result := n.Calculate([]float64{0,1,0,1,1,1,0,1,0})
Persist network
Save to file:
import "github.com/NOX73/go-neural/persist"
persist.ToFile("/path/to/file.json", network)
Load from file:
import "github.com/NOX73/go-neural/persist"
network := persist.FromFile("/path/to/file.json")
Learning
import "github.com/NOX73/go-neural/learn"
var input, idealOutput []float64
// Learning speed [0..1]
var speed float64
learn.Learn(network, in, idealOut, speed)
You can get estimate of learning quality:
e := learn.Evaluation(network, in, idealOut)
Engine
For concurrent learn, calculate & dump neural network.
network := neural.NewNetwork(2, []int{2, 2})
engine := New(network)
engine.Start()
engine.Learn([]float64{1, 2}, []float64{3, 3}, 0.1)
out := engine.Calculate([]float64{1, 2})
Live example
Dirty live example: [https://github.com/NOX73/go-neural-play]