Krzysztof Ropiak krro

## Main.java
package com.company;

import java.util.*;
import java.util.stream.Collectors;

public class Main {
    public static void main(String[] args) {

        int[] arr = {1, 2, 3, 4, 5};
        int[] arr2 = {-5, 0, 10, -5, 0, 5, 5};

## CDR.csv

          
            CDR
            20150811
            27.51
            27.95
            27.51
            27.55
            204668
            0

## mse.scala
val meanSquaredError = scoreAndLabels.map { case(l, s) => math.pow((l - s), 2) }.mean

## prediction.scala
val scoreAndLabels = testData.map { point =>
  val score = model.predict(point.features)
  (point.label, score)
}

## model.scala
val model = RidgeRegressionWithSGD.train(trainingData, numIterations, stepSize, regularizationParam)

## learningParams.scala
val numIterations = 1000
val stepSize = 0.005
val regularizationParam = 0.01

## split.scala
val Array(trainingData, testData) = labeledPointsRDD.randomSplit(Array(0.7, 0.3))

## rdd.scala
val labeledPointsRDD = sparkContext.parallelize(labeledPoints)

## labeledPoints.scala
val probesNumber = 20
val labeledPoints = for(i <- probesNumber until growths.size) yield {
  LabeledPoint(growths(i), Vectors.dense(growths.slice(i - probesNumber, i).toArray))
}

## growths.scala
val growths = prices.drop(1).zip(prices.dropRight(1)).map {
  case (current, previous) => 100.0 * (current - previous) / previous
}
	package com.company;

	import java.util.*;
	import java.util.stream.Collectors;

	public class Main {
	public static void main(String[] args) {

	int[] arr = {1, 2, 3, 4, 5};
	int[] arr2 = {-5, 0, 10, -5, 0, 5, 5};
	val scoreAndLabels = testData.map { point =>
	val score = model.predict(point.features)
	(point.label, score)
	}
	val numIterations = 1000
	val stepSize = 0.005
	val regularizationParam = 0.01
	val probesNumber = 20
	val labeledPoints = for(i <- probesNumber until growths.size) yield {
	LabeledPoint(growths(i), Vectors.dense(growths.slice(i - probesNumber, i).toArray))
	}
	val growths = prices.drop(1).zip(prices.dropRight(1)).map {
	case (current, previous) => 100.0 * (current - previous) / previous
	}