gradient_descent.example.rb

require 'csv'

# y = mx + b
# m is slope, b is y-intercept
def compute_error_for_line_given_points(b, m, points)
    totalError = 0
    0.upto points.length-1 do |i|
        x = points[i][0]
        y = points[i][1]
        totalError += (y - (m * x + b)) ** 2
    end
    return totalError / points.length
end

def step_gradient(b_current, m_current, points, learningRate)
    b_gradient = 0
    m_gradient = 0
    n = points.length + 0.0

    0.upto points.length-1 do |i|
        x = points[i][0]
        y = points[i][1]
        m_gradient += -(2/n) * x * (y - ((m_current * x) + b_current))
        b_gradient += -(2/n) * (y - ((m_current * x) + b_current))
    end
    new_m = m_current - (learningRate * m_gradient)
    new_b = b_current - (learningRate * b_gradient)
    return [new_b, new_m]
end

def gradient_descent_runner(points, starting_b, starting_m, learning_rate, num_iterations)
    b = starting_b
    m = starting_m

    0.upto num_iterations-1 do |i|
        b, m = step_gradient(b, m, points, learning_rate)
    end
    return [b, m]
end

def run()
    points = CSV.read('data.csv', converters: :numeric)
    learning_rate = 0.0001
    initial_b = 0 # initial y-intercept guess
    initial_m = 0 # initial slope guess
    num_iterations = 1000    
    puts "Starting gradient descent at b = #{initial_b}, m = #{initial_m}, error = #{compute_error_for_line_given_points(initial_b, initial_m, points)}"
    puts "Running..."
    (b, m) = gradient_descent_runner(points, initial_b, initial_m, learning_rate, num_iterations)
    puts "After #{num_iterations} iterations b = #{b}, m = #{m}, error = #{compute_error_for_line_given_points(b, m, points)}"
end

run()