}
dev.off()
names(arc) <- c("from","to","graph")
write.csv(arc,"arc.csv",row.names = F)
setwd("/home/qja0428/Dropbox/research/Yoo")
library(bnlearn)
dataset <- read.csv("test_three_variables.csv")
#make the variable as factor
dataset <- apply(dataset,2,as.factor)
dataset <- as.data.frame(dataset)
score_bde <- numeric(25)
#graph 1  A B C
g1 <- empty.graph(names(dataset))
score_bde[1] <- score(g1,data = dataset, type="bde") #-10405.17
#graph 2 A->B C
g2 <- set.arc(g1,"A","B")
score_bde[2] <- score(g2,data = dataset, type="bde") #-10408.04
#graph 3  C->A->B
g3 <- set.arc(g2,"C","A")
score_bde[3] <- score(g3,data = dataset, type="bde") #-10411.15
#graph 4 B->A<-C
g4 <- empty.graph(names(dataset))
modelstring(g4) <- "[B][C][A|B:C]"
score_bde[4] <- score(g4,data = dataset, type="bde") #-10414.47
#graph 5 B->C->A
g5 <- empty.graph(names(dataset))
modelstring(g5) <- "[B][C|B][A|C]"
score_bde[5] <- score(g5,data = dataset, type="bde") #-10411.13
#graph 6
g6 <- empty.graph(names(dataset))
modelstring(g6) <- "[B][C|B][A|C:B]"
score_bde[6] <- score(g6,data = dataset, type="bde") #-10417.33
#graph 7
g7 <- empty.graph(names(dataset))
modelstring(g7) <- "[C][A|C][B|C]"
score_bde[7] <- score(g7,data = dataset, type="bde") #-10411.13
#graph 8
g8 <- empty.graph(names(dataset))
modelstring(g8) <- "[C][A|C][B|C:A]"
score_bde[8] <- score(g8,data = dataset, type="bde") #-10417.33
#graph 9
g9 <- empty.graph(names(dataset))
modelstring(g9) <- "[C][A|C:B][B|C]"
score_bde[9] <- score(g9,data = dataset, type="bde") #-10417.33
#graph 10
g10 <- empty.graph(names(dataset))
modelstring(g10) <- "[C|A][A][B]"
score_bde[10] <- score(g10,data = dataset, type="bde") #-10408.27
#graph 11
g11 <- empty.graph(names(dataset))
modelstring(g11) <- "[C|A][A][B|A]"
score_bde[11] <- score(g11,data = dataset, type="bde") #-10411.15
#graph 12
g12 <- empty.graph(names(dataset))
modelstring(g12) <- "[A|B][B][C|A]"
score_bde[12] <- score(g12,data = dataset, type="bde") #-10411.15
#graph 13
g13 <- empty.graph(names(dataset))
modelstring(g13) <- "[A|B][B][C]"
score_bde[13] <- score(g13,data = dataset, type="bde") #-10408.04
#graph 14
g14 <- empty.graph(names(dataset))
modelstring(g14) <- "[A][B][C|A:B]"
score_bde[14] <- score(g14,data = dataset, type="bde") #-10414.45
#graph 15
g15 <- empty.graph(names(dataset))
modelstring(g15) <- "[A][B|A][C|A:B]"
score_bde[15] <- score(g15,data = dataset, type="bde") #-10417.33
#graph 16
g16 <- empty.graph(names(dataset))
modelstring(g16) <- "[A|B][B][C|A:B]"
score_bde[16] <- score(g16,data = dataset, type="bde") #-10417.33
#graph 17
g17 <- empty.graph(names(dataset))
modelstring(g17) <- "[A][B|C][C|A]"
score_bde[17] <- score(g17,data = dataset, type="bde") #-10411.13
#graph 18
g18 <- empty.graph(names(dataset))
modelstring(g18) <- "[A][B|C:A][C|A]"
score_bde[18] <- score(g18,data = dataset, type="bde") #-10417.33
#graph 19
g19 <- empty.graph(names(dataset))
modelstring(g19) <- "[A][B][C|B]"
score_bde[19] <- score(g19,data = dataset, type="bde") #-10408.03
#graph 20
g20 <- empty.graph(names(dataset))
modelstring(g20) <- "[A][B|A][C|B]"
score_bde[20] <- score(g20,data = dataset, type="bde") #-10410.9
#graph 21
g21 <- empty.graph(names(dataset))
modelstring(g21) <- "[A|B][B][C|B]"
score_bde[21] <- score(g21,data = dataset, type="bde") #-10410.9
#graph 22
g22 <- empty.graph(names(dataset))
modelstring(g22) <- "[A][B|C][C]"
score_bde[22] <- score(g22,data = dataset, type="bde") #-10408.03
#graph 23
g23 <- empty.graph(names(dataset))
modelstring(g23) <- "[A][B|C:A][C]"
score_bde[23] <- score(g23,data = dataset, type="bde") #-10414.22
#graph 24
g24 <- empty.graph(names(dataset))
modelstring(g24) <- "[A|B][B|C][C]"
score_bde[24] <- score(g24,data = dataset, type="bde") #-10410.9
#graph 25
g25 <- empty.graph(names(dataset))
modelstring(g25) <- "[A|C][B][C]"
score_bde[25] <- score(g25,data = dataset, type="bde") #-10408.27
m <- ncol(dataset)
n <- nrow(dataset)
#a function that return the variable position
position <- function(x, data) {
result <- which(x == names(data))
return(result)
}
#bde score from python
score_bde_python <- c(-10409.216534618594,
-10413.72828956955,
-10418.467521622148,
-10423.856345541608,
-10418.448531487986,
-10418.44853148799,
-10418.44853148799,
-10428.34911035841,
-10428.34911035841,
-10413.95576667119,
-10418.467521622146,
-10418.467521622146,
-10413.72828956955,
-10423.837355407451,
-10428.349110358407,
-10428.349110358407,
-10418.448531487988,
-10428.349110358407,
-10413.709299435392,
-10418.221054386348,
-10418.221054386348,
-10413.709299435392,
-10423.609878305811,
-10418.221054386351,
-10413.955766671188)
arc <- data.frame()
#output a pdf file
pdf("plot.pdf")
for (i in 1:25) {
s <- paste0("g",i)
tmp <- eval(parse(text=s))
#plot
plot(tmp,main=paste("BDe score: ", score_bde_python[i]))
}
dev.off()
g1 <- empty.graph(names(dataset))
dataset <- read.csv("test_three_variables.csv")
#make the variable as factor
dataset <- apply(dataset,2,as.factor)
dataset <- as.data.frame(dataset)
score_bde <- numeric(25)
#graph 1  A B C
g1 <- empty.graph(names(dataset))
score_bde[1] <- score(g1,data = dataset, type="bde") #-10405.17
getwd()
setwd("/home/qja0428/Dropbox/research/Yoo")
setwd("/Users/jinganqu/Dropbox/research/Yoo")
dataset <- read.csv("test_three_variables.csv")
#make the variable as factor
dataset <- apply(dataset,2,as.factor)
dataset <- as.data.frame(dataset)
score_bde <- numeric(25)
#graph 1  A B C
g1 <- empty.graph(names(dataset))
score_bde[1] <- score(g1,data = dataset, type="bde") #-10405.17
#graph 2 A->B C
g2 <- set.arc(g1,"A","B")
score_bde[2] <- score(g2,data = dataset, type="bde") #-10408.04
#graph 3  C->A->B
g3 <- set.arc(g2,"C","A")
score_bde[3] <- score(g3,data = dataset, type="bde") #-10411.15
#graph 4 B->A<-C
g4 <- empty.graph(names(dataset))
modelstring(g4) <- "[B][C][A|B:C]"
score_bde[4] <- score(g4,data = dataset, type="bde") #-10414.47
#graph 5 B->C->A
g5 <- empty.graph(names(dataset))
modelstring(g5) <- "[B][C|B][A|C]"
score_bde[5] <- score(g5,data = dataset, type="bde") #-10411.13
#graph 6
g6 <- empty.graph(names(dataset))
modelstring(g6) <- "[B][C|B][A|C:B]"
score_bde[6] <- score(g6,data = dataset, type="bde") #-10417.33
#graph 7
g7 <- empty.graph(names(dataset))
modelstring(g7) <- "[C][A|C][B|C]"
score_bde[7] <- score(g7,data = dataset, type="bde") #-10411.13
#graph 8
g8 <- empty.graph(names(dataset))
modelstring(g8) <- "[C][A|C][B|C:A]"
score_bde[8] <- score(g8,data = dataset, type="bde") #-10417.33
#graph 9
g9 <- empty.graph(names(dataset))
modelstring(g9) <- "[C][A|C:B][B|C]"
score_bde[9] <- score(g9,data = dataset, type="bde") #-10417.33
#graph 10
g10 <- empty.graph(names(dataset))
modelstring(g10) <- "[C|A][A][B]"
score_bde[10] <- score(g10,data = dataset, type="bde") #-10408.27
#graph 11
g11 <- empty.graph(names(dataset))
modelstring(g11) <- "[C|A][A][B|A]"
score_bde[11] <- score(g11,data = dataset, type="bde") #-10411.15
#graph 12
g12 <- empty.graph(names(dataset))
modelstring(g12) <- "[A|B][B][C|A]"
score_bde[12] <- score(g12,data = dataset, type="bde") #-10411.15
#graph 13
g13 <- empty.graph(names(dataset))
modelstring(g13) <- "[A|B][B][C]"
score_bde[13] <- score(g13,data = dataset, type="bde") #-10408.04
#graph 14
g14 <- empty.graph(names(dataset))
modelstring(g14) <- "[A][B][C|A:B]"
score_bde[14] <- score(g14,data = dataset, type="bde") #-10414.45
#graph 15
g15 <- empty.graph(names(dataset))
modelstring(g15) <- "[A][B|A][C|A:B]"
score_bde[15] <- score(g15,data = dataset, type="bde") #-10417.33
#graph 16
g16 <- empty.graph(names(dataset))
modelstring(g16) <- "[A|B][B][C|A:B]"
score_bde[16] <- score(g16,data = dataset, type="bde") #-10417.33
#graph 17
g17 <- empty.graph(names(dataset))
modelstring(g17) <- "[A][B|C][C|A]"
score_bde[17] <- score(g17,data = dataset, type="bde") #-10411.13
#graph 18
g18 <- empty.graph(names(dataset))
modelstring(g18) <- "[A][B|C:A][C|A]"
score_bde[18] <- score(g18,data = dataset, type="bde") #-10417.33
#graph 19
g19 <- empty.graph(names(dataset))
modelstring(g19) <- "[A][B][C|B]"
score_bde[19] <- score(g19,data = dataset, type="bde") #-10408.03
#graph 20
g20 <- empty.graph(names(dataset))
modelstring(g20) <- "[A][B|A][C|B]"
score_bde[20] <- score(g20,data = dataset, type="bde") #-10410.9
#graph 21
g21 <- empty.graph(names(dataset))
modelstring(g21) <- "[A|B][B][C|B]"
score_bde[21] <- score(g21,data = dataset, type="bde") #-10410.9
#graph 22
g22 <- empty.graph(names(dataset))
modelstring(g22) <- "[A][B|C][C]"
score_bde[22] <- score(g22,data = dataset, type="bde") #-10408.03
#graph 23
g23 <- empty.graph(names(dataset))
modelstring(g23) <- "[A][B|C:A][C]"
score_bde[23] <- score(g23,data = dataset, type="bde") #-10414.22
#graph 24
g24 <- empty.graph(names(dataset))
modelstring(g24) <- "[A|B][B|C][C]"
score_bde[24] <- score(g24,data = dataset, type="bde") #-10410.9
#graph 25
g25 <- empty.graph(names(dataset))
modelstring(g25) <- "[A|C][B][C]"
score_bde[25] <- score(g25,data = dataset, type="bde") #-10408.27
m <- ncol(dataset)
n <- nrow(dataset)
#a function that return the variable position
position <- function(x, data) {
result <- which(x == names(data))
return(result)
}
#bde score from python
score_bde_python <- c(-10409.216534618594,
-10413.72828956955,
-10418.467521622148,
-10423.856345541608,
-10418.448531487986,
-10418.44853148799,
-10418.44853148799,
-10428.34911035841,
-10428.34911035841,
-10413.95576667119,
-10418.467521622146,
-10418.467521622146,
-10413.72828956955,
-10423.837355407451,
-10428.349110358407,
-10428.349110358407,
-10418.448531487988,
-10428.349110358407,
-10413.709299435392,
-10418.221054386348,
-10418.221054386348,
-10413.709299435392,
-10423.609878305811,
-10418.221054386351,
-10413.955766671188)
arc <- data.frame()
#output a pdf file
pdf("plot.pdf")
for (i in 1:25) {
s <- paste0("g",i)
tmp <- eval(parse(text=s))
#plot
plot(tmp,main=paste("BDe score: ", score_bde_python[i]))
}
dev.off()
setwd("/Users/jinganqu/Dropbox/research/Yoo/code")
dataset <- read.csv("test_three_variables.csv")
#make the variable as factor
dataset <- apply(dataset,2,as.factor)
dataset <- as.data.frame(dataset)
score_bde <- numeric(25)
#graph 1  A B C
g1 <- empty.graph(names(dataset))
score_bde[1] <- score(g1,data = dataset, type="bde") #-10405.17
#graph 2 A->B C
g2 <- set.arc(g1,"A","B")
score_bde[2] <- score(g2,data = dataset, type="bde") #-10408.04
#graph 3  C->A->B
g3 <- set.arc(g2,"C","A")
score_bde[3] <- score(g3,data = dataset, type="bde") #-10411.15
#graph 4 B->A<-C
g4 <- empty.graph(names(dataset))
modelstring(g4) <- "[B][C][A|B:C]"
score_bde[4] <- score(g4,data = dataset, type="bde") #-10414.47
#graph 5 B->C->A
g5 <- empty.graph(names(dataset))
modelstring(g5) <- "[B][C|B][A|C]"
score_bde[5] <- score(g5,data = dataset, type="bde") #-10411.13
#graph 6
g6 <- empty.graph(names(dataset))
modelstring(g6) <- "[B][C|B][A|C:B]"
score_bde[6] <- score(g6,data = dataset, type="bde") #-10417.33
#graph 7
g7 <- empty.graph(names(dataset))
modelstring(g7) <- "[C][A|C][B|C]"
score_bde[7] <- score(g7,data = dataset, type="bde") #-10411.13
#graph 8
g8 <- empty.graph(names(dataset))
modelstring(g8) <- "[C][A|C][B|C:A]"
score_bde[8] <- score(g8,data = dataset, type="bde") #-10417.33
#graph 9
g9 <- empty.graph(names(dataset))
modelstring(g9) <- "[C][A|C:B][B|C]"
score_bde[9] <- score(g9,data = dataset, type="bde") #-10417.33
#graph 10
g10 <- empty.graph(names(dataset))
modelstring(g10) <- "[C|A][A][B]"
score_bde[10] <- score(g10,data = dataset, type="bde") #-10408.27
#graph 11
g11 <- empty.graph(names(dataset))
modelstring(g11) <- "[C|A][A][B|A]"
score_bde[11] <- score(g11,data = dataset, type="bde") #-10411.15
#graph 12
g12 <- empty.graph(names(dataset))
modelstring(g12) <- "[A|B][B][C|A]"
score_bde[12] <- score(g12,data = dataset, type="bde") #-10411.15
#graph 13
g13 <- empty.graph(names(dataset))
modelstring(g13) <- "[A|B][B][C]"
score_bde[13] <- score(g13,data = dataset, type="bde") #-10408.04
#graph 14
g14 <- empty.graph(names(dataset))
modelstring(g14) <- "[A][B][C|A:B]"
score_bde[14] <- score(g14,data = dataset, type="bde") #-10414.45
#graph 15
g15 <- empty.graph(names(dataset))
modelstring(g15) <- "[A][B|A][C|A:B]"
score_bde[15] <- score(g15,data = dataset, type="bde") #-10417.33
#graph 16
g16 <- empty.graph(names(dataset))
modelstring(g16) <- "[A|B][B][C|A:B]"
score_bde[16] <- score(g16,data = dataset, type="bde") #-10417.33
#graph 17
g17 <- empty.graph(names(dataset))
modelstring(g17) <- "[A][B|C][C|A]"
score_bde[17] <- score(g17,data = dataset, type="bde") #-10411.13
#graph 18
g18 <- empty.graph(names(dataset))
modelstring(g18) <- "[A][B|C:A][C|A]"
score_bde[18] <- score(g18,data = dataset, type="bde") #-10417.33
#graph 19
g19 <- empty.graph(names(dataset))
modelstring(g19) <- "[A][B][C|B]"
score_bde[19] <- score(g19,data = dataset, type="bde") #-10408.03
#graph 20
g20 <- empty.graph(names(dataset))
modelstring(g20) <- "[A][B|A][C|B]"
score_bde[20] <- score(g20,data = dataset, type="bde") #-10410.9
#graph 21
g21 <- empty.graph(names(dataset))
modelstring(g21) <- "[A|B][B][C|B]"
score_bde[21] <- score(g21,data = dataset, type="bde") #-10410.9
#graph 22
g22 <- empty.graph(names(dataset))
modelstring(g22) <- "[A][B|C][C]"
score_bde[22] <- score(g22,data = dataset, type="bde") #-10408.03
#graph 23
g23 <- empty.graph(names(dataset))
modelstring(g23) <- "[A][B|C:A][C]"
score_bde[23] <- score(g23,data = dataset, type="bde") #-10414.22
#graph 24
g24 <- empty.graph(names(dataset))
modelstring(g24) <- "[A|B][B|C][C]"
score_bde[24] <- score(g24,data = dataset, type="bde") #-10410.9
#graph 25
g25 <- empty.graph(names(dataset))
modelstring(g25) <- "[A|C][B][C]"
score_bde[25] <- score(g25,data = dataset, type="bde") #-10408.27
m <- ncol(dataset)
n <- nrow(dataset)
#a function that return the variable position
position <- function(x, data) {
result <- which(x == names(data))
return(result)
}
#bde score from python
score_bde_python <- c(-10409.216534618594,
-10413.72828956955,
-10418.467521622148,
-10423.856345541608,
-10418.448531487986,
-10418.44853148799,
-10418.44853148799,
-10428.34911035841,
-10428.34911035841,
-10413.95576667119,
-10418.467521622146,
-10418.467521622146,
-10413.72828956955,
-10423.837355407451,
-10428.349110358407,
-10428.349110358407,
-10418.448531487988,
-10428.349110358407,
-10413.709299435392,
-10418.221054386348,
-10418.221054386348,
-10413.709299435392,
-10423.609878305811,
-10418.221054386351,
-10413.955766671188)
arc <- data.frame()
#output a pdf file
pdf("plot.pdf")
for (i in 1:25) {
s <- paste0("g",i)
tmp <- eval(parse(text=s))
#plot
plot(tmp,main=paste("BDe score: ", score_bde_python[i]))
}
dev.off()
pdf("plot.pdf")
for (i in 1:25) {
s <- paste0("g",i)
tmp <- eval(parse(text=s))
#plot
plot(tmp,main=paste("BDe score (python): ", score_bde_python[i]),
"\n","BDe score (r): ",score_bde[i])
}
dev.off()
paste("BDe score (python): ", score_bde_python[i]),
"\n","BDe score (r): ",score_bde[i]
paste("BDe score (python): ", score_bde_python[i]),
"\\n","BDe score (r): ",score_bde[i]
paste("BDe score (python): ", score_bde_python[i]),
"\n","BDe score (r): ",score_bde[i]
paste("BDe score (python): ", score_bde_python[i]),
"\n","BDe score (r): ",score_bde[i]
paste("BDe score (python): ", score_bde_python[i]),"\n","BDe score (r): ",score_bde[i]
paste("BDe score (python): ", score_bde_python[i])
paste("BDe score (python): ", score_bde_python[i]),
"\nBDe score (r): ", score_bde[i]
paste("X:",1," ","Y:", 2," ","\nZ:",3)
paste("BDe score (python): ", score_bde_python[i]),
"\nBDe score (r): ", score_bde[i]
paste("BDe score (python): ", score_bde_python[i]),
"\nBDe score (r): "
paste("BDe score (python): ", score_bde_python[i]),
paste("BDe score (python): ", score_bde_python[i],
"\nBDe score (r): ", score_bde[i])
pdf("plot.pdf")
for (i in 1:25) {
s <- paste0("g",i)
tmp <- eval(parse(text=s))
#plot
plot(tmp,main=paste("BDe score (python): ", score_bde_python[i],
"\nBDe score (r): ", score_bde[i]))
}
dev.off()
score_bde - score_bde_python
colnames(combined)[2] <- "Games"
colnames(combined)[3] <- "OffPPG"
colnames(combined)[4] <- "OffYPG"
colnames(combined)[5] <- "OffPassYPG"
colnames(combined)[6] <- "OffRushYPG"
combined$G.y <- NULL
colnames(combined)[15] <- "DefPPG"
combined
colnames(combined)[15] <- "DefPPG"
colnames(combined)[16] <- "DefYPG"
colnames(combined)[17] <- "DefRushYPG"
colnames(combined)[18] <- "DefPassYPG"
hist(combined$OffPPG, breaks=10, main="Offensive Points Per
Game", xlab="Offensive PPG",ylab="Number of Teams")
mean(combined$OffPPG)
offense$OPassStrength <- max(offense[,5])-offense[,5]
offense$OPassStrength <- (1-(offense$OPassStrength/max(offense$OPassStrength)))*100
offense$OPassStrength
head(offense)