analysis.R

setwd('D:/cs229')
library(xlsx)
library(ggplot2)

library(car)
dat=read.xlsx("results.xlsx",sheetName='Sheet1')
attach(dat)
fit=lm(Acc~as.factor(ALG)+Data_size+as.factor(Embedding),data=dat)
summary(fit)
anova(fit)
dat
#plot(fit)
#plot(dat)


diagPlot<-function(model){
  p1<-ggplot(model, aes(.fitted, .resid))+geom_point()
  p1<-p1+stat_smooth(method="loess")+geom_hline(yintercept=0, col="red", linetype="dashed")
  p1<-p1+xlab("Fitted values")+ylab("Residuals")
  p1<-p1+ggtitle("Residual vs Fitted Plot")+theme_bw()
  p2<-ggplot(model, aes(qqnorm(.stdresid)[[1]], .stdresid))+geom_point(na.rm = TRUE)+geom_smooth(method = "lm",se = TRUE)
  p2<-p2+geom_abline()+xlab("Theoretical Quantiles")+ylab("Standardized Residuals")
  p2<-p2+ggtitle("Normal Q-Q")+theme_bw()
  p3<-ggplot(model, aes(.fitted, sqrt(abs(.stdresid))))+geom_point(na.rm=TRUE)
  p3<-p3+stat_smooth(method="loess", na.rm = TRUE)+xlab("Fitted Value")
  p3<-p3+ylab(expression(sqrt("|Standardized residuals|")))
  p3<-p3+ggtitle("Scale-Location")+theme_bw()
  p4<-ggplot(model, aes(seq_along(.cooksd), .cooksd))+geom_bar(stat="identity", position="identity")
  p4<-p4+xlab("Obs. Number")+ylab("Cook's distance")
  p4<-p4+ggtitle("Cook's distance")+theme_bw()
  p5<-ggplot(model, aes(.hat, .stdresid))+geom_point(aes(size=.cooksd), na.rm=TRUE)
  p5<-p5+stat_smooth(method="loess", na.rm=TRUE)
  p5<-p5+xlab("Leverage")+ylab("Standardized Residuals")
  p5<-p5+ggtitle("Residual vs Leverage Plot")
  p5<-p5+scale_size_continuous("Cook's Distance", range=c(1,5))
  p5<-p5+theme_bw()+theme(legend.position="bottom")
  p6<-ggplot(model, aes(.hat, .cooksd))+geom_point(na.rm=TRUE)+stat_smooth(method="loess", na.rm=TRUE)
  p6<-p6+xlab("Leverage hii")+ylab("Cook's Distance")
  p6<-p6+ggtitle("Cook's dist vs Leverage hii/(1-hii)")
  p6<-p6+geom_abline(slope=seq(0,3,0.5), color="gray", linetype="dashed")
  p6<-p6+theme_bw()
  return(list(rvfPlot=p1, qqPlot=p2, sclLocPlot=p3, cdPlot=p4, rvlevPlot=p5, cvlPlot=p6))}
 
  
 diagPlot(fit)

 crPlots(fit)