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//: Playground - noun: a place where people can play | |
import Foundation | |
protocol Neuron { | |
var weights: [Double] {get} | |
func feedforward(input: [Double]) -> Double | |
func activation(input: Double) -> Double | |
} | |
extension Neuron { | |
func feedforward(input: [Double]) -> Double { | |
return activation(zip(input, weights).reduce(0) { $0 + $1.0 * $1.1 }) | |
} | |
} | |
protocol TrainableNeuron: Neuron { | |
var weights: [Double] {get set} | |
var learningConstant: Double { get } | |
mutating func train(input: [Double], desired: Double) | |
} | |
extension TrainableNeuron { | |
var learningConstant: Double { return 0.01 } | |
mutating func train(input: [Double], desired: Double) { | |
let result = feedforward(input) | |
let error = desired - result | |
weights = zip(weights, input).map{$0 + $1 * error * self.learningConstant} | |
} | |
} | |
class Perceptron: TrainableNeuron { | |
var weights: [Double] | |
init(inputsCount: Int) { | |
weights = (1...inputsCount).map{_ in Double(random() % 11)/10.0} | |
print(weights) | |
} | |
func activation(input: Double) -> Double { | |
return input > 0.0 ? 1.0 : -1.0 | |
} | |
} | |
func f(x: Double) -> Double { | |
return 2.0*x + 1.0 | |
} | |
func generatePoint() -> (Double, Double) { | |
let x = Double(random() % 640) * Double(random() % 2 == 0 ? 1 : -1) | |
let y = Double(random() % 480) * Double(random() % 2 == 0 ? 1 : -1) | |
return (x, y) | |
} | |
func generateTrainingSet(size: Int) -> [([Double], Double)] { | |
return (1...size).map{ _ in | |
let (x, y) = generatePoint() | |
let yLine = f(x) | |
return ([x, y, 1], y < yLine ? -1.0 : 1.0) | |
} | |
} | |
extension TrainableNeuron { | |
mutating func train(trainingSet: [([Double], Double)]) { | |
trainingSet.forEach{self.train($0.0, desired: $0.1)} | |
} | |
} | |
var n = Perceptron(inputsCount: 3) | |
let ts = generateTrainingSet(3000) | |
n.train(ts) | |
print(n.weights) | |
let points = (1...10).map{_ in generatePoint()} | |
for (x, y) in points { | |
let yLine = f(x) | |
let desired = y < yLine ? -1.0 : 1.0 | |
let actual = n.feedforward([x, y, 1]) | |
if desired == actual { | |
print("point(\(x), \(y)): success") | |
} else { | |
print("point(\(x), \(y)): fail") | |
} | |
} |
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