aboutsummaryrefslogtreecommitdiff
path: root/examples/src/main/scala/LocalLR.scala
diff options
context:
space:
mode:
Diffstat (limited to 'examples/src/main/scala/LocalLR.scala')
-rw-r--r--examples/src/main/scala/LocalLR.scala41
1 files changed, 41 insertions, 0 deletions
diff --git a/examples/src/main/scala/LocalLR.scala b/examples/src/main/scala/LocalLR.scala
new file mode 100644
index 0000000000..175907e551
--- /dev/null
+++ b/examples/src/main/scala/LocalLR.scala
@@ -0,0 +1,41 @@
+import java.util.Random
+import Vector._
+
+object LocalLR {
+ val N = 10000 // Number of data points
+ val D = 10 // Numer of dimensions
+ val R = 0.7 // Scaling factor
+ val ITERATIONS = 5
+ val rand = new Random(42)
+
+ case class DataPoint(x: Vector, y: Double)
+
+ def generateData = {
+ def generatePoint(i: Int) = {
+ val y = if(i % 2 == 0) -1 else 1
+ val x = Vector(D, _ => rand.nextGaussian + y * R)
+ DataPoint(x, y)
+ }
+ Array.fromFunction(generatePoint _)(N)
+ }
+
+ def main(args: Array[String]) {
+ val data = generateData
+
+ // Initialize w to a random value
+ var w = Vector(D, _ => 2 * rand.nextDouble - 1)
+ println("Initial w: " + w)
+
+ for (i <- 1 to ITERATIONS) {
+ println("On iteration " + i)
+ var gradient = Vector.zeros(D)
+ for (p <- data) {
+ val scale = (1 / (1 + Math.exp(-p.y * (w dot p.x))) - 1) * p.y
+ gradient += scale * p.x
+ }
+ w -= gradient
+ }
+
+ println("Final w: " + w)
+ }
+}