'再抽一次','20元','蹲起',
'拍肚皮','抄ID','蹲起',
'随机周边','亲亲','tui',
'等身抱枕','贴纸条','语癖卷',
'抄ID','咕咕咕','随机周边',
'加班30分','加班30分','蹲起'
)
b<-sample(a,36)
print(matrix(b,nrow=6))
cat(b)
summmary(b)
summary(b)
summary(a)
b<-factor(b)
summary(b)
a<-c('语癖卷','SC歌曲卷','遥控器体验卡','贴怪图','遥控器体验卡',
'随机周边','连麦卡','指压板','指压板','指压板',
'抄ID','加班卷','抄ID','禁言卷','拷打卷',
'口水卷','口水卷','撒娇八连','语癖卷','再抽一次',
'加班卷','夹子音','抱枕或3D鼠标垫','随机周边','御姐音'
)
b<-sample(a,25)
print(matrix(b,nrow=5))
cat(b)
source("~/gugu2.R", encoding = 'UTF-8')
a<-c('语癖卷','SC歌曲卷','遥控器体验卡','贴怪图','遥控器体验卡',
'随机周边','连麦卡','指压板','指压板','指压板',
'抄ID','加班卷','抄ID','禁言卷','拷打卷',
'口水卷','SC歌曲卷','撒娇八连','语癖卷','再抽一次',
'加班卷','夹子音','抱枕或3D鼠标垫','随机周边','御姐音'
)
b<-sample(a,25)
print(matrix(b,nrow=5))
cat(b)
2390/2
1195/23
1195/25
1195/40
1195/45
1195/30
1195/15
1195/5
sqrt(1699e8)
source("D:/database/SynologyDrive/working/part2effort-aware/simulation/simulate2023_4.R")
source("D:/database/SynologyDrive/working/ISSTA2024/code/simulate2023_5.R")
p1<-ggplot(data=y.up,aes(y.skew, y.acc)) #here
p1+geom_point(aes(colour = factor(Rep)))+geom_vline(xintercept = 3.85)
source("D:/database/SynologyDrive/working/ISSTA2024/code/simulate2023_5.R")
p1<-ggplot(data=y.up,aes(y.skew, y.acc)) #here
p1+geom_point(aes(colour = factor(Rep)))+geom_vline(xintercept = median(y.skew))
p1+geom_point())+geom_vline(xintercept = median(y.skew))
p1+geom_point()+geom_vline(xintercept = median(y.skew))
p1+geom_line()+geom_vline(xintercept = median(y.skew))
p1+geom_line()
p1+geom_line()+xlab("Recall20")+ylab("Skewness")+ggtitle("Simulation")
p1+geom_line()+xlab("Recall20")+ylab("Skewness")+ggtitle("Simulation")+theme_minimal()
p1+geom_line()+xlab("Recall20")+ylab("Skewness")+ggtitle("Simulation one time")
p1+geom_line()+xlab("Recall20")+ylab("Skewness")+ggtitle("Simulation one time")+
theme(plot.title = element_text(hjust = 0.5))
p1+geom_line()+xlab("Recall20")+ylab("Skewness")+ggtitle("Simulation Once")+
theme(plot.title = element_text(hjust = 0.5))
p1+geom_line()+xlab("Recall20")+ylab("Skewness")+ggtitle("Simulation once")+
theme(plot.title = element_text(hjust = 0.5))
p1+geom_line()+xlab("Skewness")+ylab("Recall20")+ggtitle("Simulation once")+
theme(plot.title = element_text(hjust = 0.5))
p1+geom_line()+xlab("Skewness")+ylab("Recall20")+ggtitle("Performance of EA-up (Simulate once)")+
theme(plot.title = element_text(hjust = 0.5))
p1+geom_line()+xlab("Skewness")+ylab("Recall@20")+ggtitle("Performance of EA-up (Simulate once)")+
theme(plot.title = element_text(hjust = 0.5))
p1+geom_line()+xlab("Skewness")+ylab("Recall@20%")+ggtitle("Performance of EA-up (Simulate once)")+
theme(plot.title = element_text(hjust = 0.5))
p1<-ggplot(data=y.up,aes(y.skew, y.popt)) #here
p1+geom_line()+xlab("Skewness")+ylab("Popt")+ggtitle("Performance of EA-up (Simulate once)")+
theme(plot.title = element_text(hjust = 0.5))
8000*25
8*25
71-6
(71-6)*150
(71-7)*150
(71-8)*150
(260-80)/20
7400/150
log(3.28)
log(3.28,10)
log(3.28,10)/10
log(7,10)/10
help(log)
log10(7)/10
log10(140)/10
log10(140)/20
log10(6)/20
log10(7)/20
log(7.100)
log(7,100)
log(7,2)
log(7,1000)
log(7,1e3)
log(7,1e5)
log(7,1e7)
log(7,1e10)
log(140,1e10)
log(140,1e20)
log(7,1e20)
log(3,1e20)
log(1,1e20)
log(1.2,1e20)
log(3+1,1e20)
log(4)
log(1.1)
log(3)
log(4.28)
log(4.28)/10
log(4.28)/20
log(4.28)/30
log(8.28)/30
log(8.28)/40
log(4.28)/40
log(5.28)/40
log(9.28)/40
log(140)/40
log(142)/40
log(142)/50
log(9.28)/50
log(3.28)/50
180/12
24-15
9*12
12*24
devtools::install_github("klainfo/ScottKnottESD", ref="development")
devtools::install_github("klainfo/ScottKnottESD", ref="development")
devtools::install_github("klainfo/ScottKnottESD", ref="development", force=TRUE)
5+4+3+5+3+3+4+3+3+4+4
41+5+6+20
13800/150
50+120+71+20+68+65
394/6
16*60
12*24+120
12*24+120+75*4
150*10
150*15
0.0884/0.03491
0.0884/0.03491*100
0.00884/0.03491*100
.00365/.01899
140*150
(155-19)*150
16720/150
255-21)
(255-21)*150
17400/150
2280*0.15
160-9
151*150
900-864
18*2
28000/4
200/6
200000/6000
627267/60/60/24
3800*30/60/60
6800*64/60/60
8338/60/60
8338/60/60*100/24
a<-0.1033
b<-0.0856
print((a-b)/a)
1780*5
# 10
setwd("D:/database/SynologyDrive/working/Dr.Thesis/rcode")
#
#step[2] MCC vs log(IR,2)
#
Edata <- read.table("rawdata_18APR2018.csv",header=T,sep=",")
library(ggplot2)
m2<-3.94
Edata$IR<-Edata$ImbLevel
data1<-subset(Edata, ImbLearner=="N")
summary(data1)
p1<-ggplot(data1, aes(log(IR,2), MCC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡     <-------|------->     中高不均衡",
x = 2.07, y = 0.7, size = 4, colour = "purple")
png(filename = paste("IR与MCC.png",sep=""),
width = 900, height = 675, res = 200)
print(p1)
dev.off()
p1<-ggplot(data1, aes(log(IR,2), AUC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡     <-------|------->     中高不均衡",
x = 2.07, y = 0.7, size = 4, colour = "purple")
png(filename = paste("IR与AUC.png",sep=""),
width = 900, height = 675, res = 200)
print(p1)
dev.off()
library(WRS2)
pbcor(data1$MCC, log(data1$IR,2))
pbcor(data1$AUC, log(data1$IR,2))
# 10
setwd("D:/database/SynologyDrive/working/Dr.Thesis/rcode")
#
#step[2] MCC vs log(IR,2)
#
Edata <- read.table("rawdata_18APR2018.csv",header=T,sep=",")
library(ggplot2)
m2<-3.94
Edata$IR<-Edata$ImbLevel
data1<-subset(Edata, ImbLearner=="N")
summary(data1)
p1<-ggplot(data1, aes(log(IR,2), MCC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡     <-------|------->     中高不均衡",
x = 2.07, y = 0.7, size = 4, colour = "purple")
png(filename = paste("IR与MCC.png",sep=""),
width = 900, height = 675, res = 200)
print(p1)
dev.off()
p1<-ggplot(data1, aes(log(IR,2), AUC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡     <-------|------->     中高不均衡",
x = 2.07, y = 0.7, size = 4, colour = "purple")
png(filename = paste("IR与AUC.png",sep=""),
width = 900, height = 675, res = 200)
print(p1)
dev.off()
library(WRS2)
pbcor(data1$MCC, log(data1$IR,2))
pbcor(data1$AUC, log(data1$IR,2))
print(p1)
p1<-ggplot(data1, aes(log(IR,2), AUC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡     <-------|------->     中高不均衡",
x = 2.07, y = 0.9, size = 4, colour = "purple")
png(filename = paste("IR与AUC.png",sep=""),
width = 900, height = 675, res = 200)
print(p1)
dev.off()
print(p1)
p1<-ggplot(data1, aes(log(IR,2), AUC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡     <-------|------->     中高不均衡",
x = 2.07, y = 0.4, size = 4, colour = "purple")
png(filename = paste("IR与AUC.png",sep=""),
width = 900, height = 675, res = 200)
print(p1)
dev.off()
print(p1)
p1<-ggplot(data1, aes(log(IR,2), AUC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡     <-------|------->     中高不均衡",
x = 2.07, y = 0.35, size = 4, colour = "purple")
png(filename = paste("IR与AUC.png",sep=""),
width = 900, height = 675, res = 200)
print(p1)
dev.off()
print(p1)
p1<-ggplot(data1, aes(log(IR,2), AUC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡     <-------|------->     中高不均衡",
x = 2.07, y = 0.95, size = 4, colour = "purple")
png(filename = paste("IR与AUC.png",sep=""),
width = 900, height = 675, res = 200)
print(p1)
dev.off()
print(p1)
p1<-ggplot(data1, aes(log(IR,2), AUC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡     <-------|------->     中高不均衡",
x = 2.07, y = 0.92, size = 4, colour = "purple")
png(filename = paste("IR与AUC.png",sep=""),
width = 900, height = 675, res = 200)
print(p1)
dev.off()
print(p1)
p1<-ggplot(data1, aes(log(IR,2), AUC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡     <-------|------->     中高不均衡",
x = 2.07, y = 0.93, size = 4, colour = "purple")
png(filename = paste("IR与AUC.png",sep=""),
width = 900, height = 675, res = 200)
print(p1)
dev.off()
print(p1)
print(p1)
#
#step[2] MCC vs log(IR,2)
#
Edata <- read.table("rawdata_18APR2018.csv",header=T,sep=",")
library(ggplot2)
m2<-3.94
Edata$IR<-Edata$ImbLevel
data1<-subset(Edata, ImbLearner=="N")
summary(data1)
p1<-ggplot(data1, aes(log(IR,2), MCC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡 <-------|------->     中高不均衡",
x = 2.07, y = 0.7, size = 4, colour = "purple")
png(filename = paste("IR与MCC.png",sep=""),
width = 900, height = 675, res = 200)
print(p1)
dev.off()
p1<-ggplot(data1, aes(log(IR,2), AUC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡 <-------|------->     中高不均衡",
x = 2.07, y = 0.93, size = 4, colour = "purple")
png(filename = paste("IR与AUC.png",sep=""),
width = 900, height = 675, res = 200)
print(p1)
dev.off()
summary(data1)
p1<-ggplot(data1, aes(log(IR,2), MCC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡 <-------|------->     中高不均衡",
x = 2.07, y = 0.7, size = 4, colour = "purple")
png(filename = paste("IR与MCC.png",sep=""),
width = 900, height = 675, res = 180)
print(p1)
dev.off()
p1<-ggplot(data1, aes(log(IR,2), AUC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡 <-------|------->     中高不均衡",
x = 2.07, y = 0.93, size = 4, colour = "purple")
png(filename = paste("IR与AUC.png",sep=""),
width = 900, height = 675, res = 180)
print(p1)
dev.off()
#
#step[2] MCC vs log(IR,2)
#
Edata <- read.table("rawdata_18APR2018.csv",header=T,sep=",")
library(ggplot2)
m2<-3.94
Edata$IR<-Edata$ImbLevel
data1<-subset(Edata, ImbLearner=="N")
summary(data1)
p1<-ggplot(data1, aes(log(IR,2), MCC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡  <-------|------->     中高不均衡",
x = 2.07, y = 0.7, size = 4, colour = "purple")
png(filename = paste("IR与MCC.png",sep=""),
width = 900, height = 675, res = 180)
print(p1)
dev.off()
View(data1)
p1<-ggplot(data1, aes(log(IR,2), MCC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡  <-------|------->     中高不均衡",
x = 2.07, y = 0.7, size = 4, colour = "purple")
print(p1)
summary(data1)
p1<-ggplot(data1, aes(log(IR,2), MCC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡  <-------|------->     中高不均衡",
x = 2.07, y = 0.7, size = 4, colour = "purple")
png(filename = paste("IR与MCC.png",sep=""),
width = 900, height = 675, res = 180)
print(p1)
dev.off()
p1<-ggplot(data1, aes(log(IR,2), AUC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡  <-------|------->     中高不均衡",
x = 2.07, y = 0.93, size = 4, colour = "purple")
png(filename = paste("IR与AUC.png",sep=""),
width = 900, height = 675, res = 180)
print(p1)
dev.off()
# 10
setwd("D:/database/SynologyDrive/working/Dr.Thesis/rcode")
#
#step[2] MCC vs log(IR,2)
#
Edata <- read.table("rawdata_18APR2018.csv",header=T,sep=",")
library(ggplot2)
m2<-3.94
Edata$IR<-Edata$ImbLevel
data1<-subset(Edata, ImbLearner=="N")
summary(data1)
p1<-ggplot(data1, aes(log(IR,2), MCC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡    <-------|------->     中高不均衡",
x = 2.07, y = 0.7, size = 4, colour = "purple")
png(filename = paste("IR与MCC.png",sep=""),
width = 900, height = 675, res = 180)
print(p1)
dev.off()
p1<-ggplot(data1, aes(log(IR,2), AUC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡    <-------|------->     中高不均衡",
x = 2.07, y = 0.93, size = 4, colour = "purple")
png(filename = paste("IR与AUC.png",sep=""),
width = 900, height = 675, res = 180)
print(p1)
dev.off()
#
#step[2] MCC vs log(IR,2)
#
Edata <- read.table("rawdata_18APR2018.csv",header=T,sep=",")
library(ggplot2)
m2<-3.94
Edata$IR<-Edata$ImbLevel
data1<-subset(Edata, ImbLearner=="N")
summary(data1)
p1<-ggplot(data1, aes(log(IR,2), MCC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡    <-------|------->     中高不均衡",
x = 2.07, y = 0.7, size = 4, colour = "purple")
png(filename = paste("IR与MCC.png",sep=""),
width = 900, height = 675, res = 180)
print(p1)
dev.off()
p1<-ggplot(data1, aes(log(IR,2), AUC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡    <-------|------->     中高不均衡",
x = 2.07, y = 0.93, size = 4, colour = "purple")
png(filename = paste("IR与AUC.png",sep=""),
width = 900, height = 675, res = 180)
print(p1)
dev.off()
print(p1)
summary(data1)
p1<-ggplot(data1, aes(log(IR,2), MCC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡    <-------|------->     中高不均衡",
x = 2.08, y = 0.7, size = 4, colour = "purple")
png(filename = paste("IR与MCC.png",sep=""),
width = 900, height = 675, res = 180)
print(p1)
dev.off()
print(p1)
p1<-ggplot(data1, aes(log(IR,2), AUC))+geom_point()+
scale_shape(solid = FALSE)+geom_smooth(method="loess")+
geom_vline(xintercept = log(m2,2),color="purple",linetype = 2)+
xlab(expression(log[2](I[R])))+
annotate("text", label = "低不均衡    <-------|------->     中高不均衡",
x = 2.08, y = 0.93, size = 4, colour = "purple")
png(filename = paste("IR与AUC.png",sep=""),
width = 900, height = 675, res = 180)
print(p1)
dev.off()
library(orddom)
# 9
setwd("D:/database/EASE2024_Replication_package")
# 6
setwd("D:/database/SynologyDrive/working/ISSTA2024/241code_data")
# 9
setwd("D:/database/EASE2024_Replication_package")
a<-runif(10
)
quantile(a)
e.qs<-quantile(a)
e.qs[1]
e.qs[2]
debugSource("D:/database/EASE2024_Replication_package/exeMain_v7trim.r")
debugSource("D:/database/EASE2024_Replication_package/exeMain_v7trim.r")
debugSource("D:/database/EASE2024_Replication_package/exeMain_v7trim.r")
debugSource("D:/database/EASE2024_Replication_package/exeMain_v7trim.r")
e.fence
e.loc
e.loc>e.fence
sum(e.loc>e.fence)
setwd("D:/database/EASE2024_Replication_package/EASE2024_Replication_package")
source("D:/database/EASE2024_Replication_package/EASE2024_Replication_package/exeMain_v7b5.r")
source("D:/database/EASE2024_Replication_package/EASE2024_Replication_package/Step_before_v7b5.r")
source("D:/database/EASE2024_Replication_package/EASE2024_Replication_package/exeMain_v7b5.r")
source("D:/database/EASE2024_Replication_package/EASE2024_Replication_package/exeMain_v7b5.r")
source("D:/database/EASE2024_Replication_package/EASE2024_Replication_package/exeMain_v7b5.r")
