7/17/2019 Task1

http://slidepdf.com/reader/full/task1-568ef52055fdc 1/2

setwd("C:/Users/fng134/Dropbox/KTH/Management/")##install.packages("stats")library(stats)periodic.x=read.csv("X.csv")periodic.y=read.csv("Y.csv")

y1=periodic.y$DispFramesy2=periodic.y$NoAudioPlayedy3=periodic.y$NoRTPPkts

xx=periodic.x[c("all_..usr","X..memused","X..swpused","proc.s","cswch.s","file.nr","sum_intr.s","rtps","ldavg.1","tcpsck","bread.s","pgfree.s")]

x=model.matrix(~.,xx)[,-1]#y=subset(periodic.y, select = c("DispFrames") )

set.seed(0)train=sample(50000,35000)

test=(-train)

##### Y1 prediction

Exectime <- proc.time()

lm.fit = lm(y1~ x,subset = train)xf=data.frame(x[test,])xtest=x[test,]

ypredic=predict(lm.fit,xf)

proc.time() - Exectime

plot(ypredic[test],col="blue")

par=(new=T)lines(y1[test],col="red")

resY1=(sum(abs(y1[test]-ypredic[test]))/15000)/mean(y1[test])cat(resY1)

### For Y2

lm.fit = lm(y2~ x,subset = train)

y2predic=predict(lm.fit,xf)

plot(y2predic[test],col="blue")par=(new=T)lines(y2[test],col="red")

res=(sum(abs(y2[test]-y2predic[test]))/15000)/mean(y2[test])cat(res)

### For Y3

7/17/2019 Task1

http://slidepdf.com/reader/full/task1-568ef52055fdc 2/2

lm.fit = lm(y3~ x,subset = train)

y3predic=predict(lm.fit,xf)

plot(y3predic[test],col="blue")par=(new=T)lines(y3[test],col="red")

resY3=(sum(abs(y3[test]-y3predic[test]))/15000)/mean(y3[test])cat(resY3)