in Allgemein, Tutorials |

Gradient Decent with Scala

Currently I’m watching a Scala and a Maschine Learning course on coursera.org and
wanted to try some simple stuff for myself. I choose Gradient Decent would be a
perfect start to try some functional programming.

The code

import scala.math._
 
object GradientDecent extends App {
 
  val alpha = 0.1 //size of steps taken in gradient decent
  val samples = List((Vector(0.0, 0.0), 2.0), (Vector(3.0, 1.0), 12.0), (Vector(2.0, 2.0), 18.0))
 
  var tetas = Vector(0.0, 0.0, 0.0)
  for (i 
        teta - (alpha / samples.size) * samples.foldLeft(0.0) {
          case (sum, (x, y)) => decentTerm(sum, 1, x, y, tetas)
        }
      case (teta, i) =>
        teta - (alpha / samples.size) * samples.foldLeft(0.0) {
          case (sum, (x, y)) => decentTerm(sum, x(i - 1), x, y, tetas)
        }
    }
  }
 
  def decentTerm(sum: Double, x_j: Double, x: Vector[Double], y: Double, tetas: Vector[Double]) = {
    sum + x_j * (h(x, tetas) - y)
  }
 
  def h(x: Vector[Double], teta: Vector[Double]): Double = {
    teta(0) + {
      for (i  sum + x)
  }
 
}

And thats pretty much everything. This is just a first version and I’m sure somebody would find ways
to optimize it. However even this hacked version is very short and handsome 🙂

Update
The code snippet here is a gradient decent for performing linear regression.

Veröffentlicht

Kommentare sind nicht mehr möglich