// The Nature of Code

// http://natureofcode.com

​

// Simple Perceptron Example

// See: http://en.wikipedia.org/wiki/Perceptron

​

// Perceptron Class

​

// Perceptron is created with n weights and learning constant

class Perceptron {

  constructor(n, c) {

    // Array of weights for inputs

    this.weights = new Array(n);

    // Start with random weights

    for (let i = 0; i < this.weights.length; i++) {

      this.weights[i] = random(-1, 1);

    }

    this.c = c; // learning rate/constant

  }

​

  // Function to train the Perceptron

  // Weights are adjusted based on "desired" answer

  train(inputs, desired) {

    // Guess the result

    let guess = this.feedforward(inputs);

    // Compute the factor for changing the weight based on the error

    // Error = desired output - guessed output

    // Note this can only be 0, -2, or 2

    // Multiply by learning constant

    let error = desired - guess;

    // Adjust weights based on weightChange * input

    for (let i = 0; i < this.weights.length; i++) {

      this.weights[i] += this.c * error * inputs[i];

    }

  }

​

  // Guess -1 or 1 based on input values

  feedforward(inputs) {

    // Sum all values

    let sum = 0;

    for (let i = 0; i < this.weights.length; i++) {

      sum += inputs[i] * this.weights[i];

    }

    // Result is sign of the sum, -1 or 1

    return this.activate(sum);

  }

​

  activate(sum) {

    if (sum > 0) return 1;

    else return -1;

  }

​

  // Return weights

  getWeights() {

    return this.weights;

  }

}