org.apache.spark.examples.LocalFileLR.scala Maven / Gradle / Ivy

Go to download
/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.apache.spark.examples

import java.util.Random
import org.apache.spark.util.Vector

object LocalFileLR {
  val D = 10   // Numer of dimensions
  val rand = new Random(42)

  case class DataPoint(x: Vector, y: Double)

  def parsePoint(line: String): DataPoint = {
    val nums = line.split(' ').map(_.toDouble)
    return DataPoint(new Vector(nums.slice(1, D+1)), nums(0))
  }

  def main(args: Array[String]) {
    val lines = scala.io.Source.fromFile(args(0)).getLines().toArray
    val points = lines.map(parsePoint _)
    val ITERATIONS = args(1).toInt

    // 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 <- points) {
        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)
  }
}