I want to add the titanic predictive analysis algorithm

[ghost]

Hi i'm a South-Korean university student studying data science. I'm interested in Titanic data analysis. Your project is the best Titanic prediction algorithm I have ever seen. It was a great help to study. So I would like to send you the R code I analyzed(association rule, Regression analysis )

Titanic dataset.zip

`data<- read.csv("file location", header=T, na.strings=c("."))
data$survived <- factor(data$survived,levels=c(1,0),labels = c("y","n"))
data$pclass <- factor(data$pclass,levels=c(1,2,3),labels = c("1 grade","2 grade","3 grade"))
data$sibsp <- factor(data$sibsp,levels=c(0,1,2,3,4,5,8),labels = c("0","1","2","3","4","5","8"))
data$parch <- factor(data$parch,levels=c(0,1,2,3,4,5,6,9),labels = c("0","1","2","3","4","5","6","9"))
data <- data.frame(data$survived,data$pclass,data$sex,data$sibsp,data$parch,data$embarked,
data$age1,data$fare1)
#association rule

summary(data)
install.packages("arules")
library(arules)
rules.all <- apriori(data)

inspect(rules.all)

rules <- apriori(data,
control = list(verbose=F),
parameter = list(minlen = 2, supp = 0.005, conf=0.8),
appearance = list(rhs=c("data.survived=n",
"data.survived=y"),
default="lhs"))

quality(rules) <- round(quality(rules),digits=3)

rules.sorted <- sort(rules, by = "lift")

inspect(rules.sorted[1:2])

subset.matrix <- is.subset(rules.sorted, rules.sorted)
subset.matrix

redundant <- colSums(subset.matrix) > 0
redundant

rules.pruned <- rules.sorted[!redundant]
inspect(rules.pruned)

inspect(rules.pruned[1])

rules_1 <- apriori(data,
control = list(verbose=F),
parameter = list(minlen = 2, supp = 0.002, conf=0.2),
appearance = list(rhs=c("data.survived=n"),
lhs=c("data.pclass=1 grade",
"data.pclass=2 grade",
"data.pclass=3 grade",
"data.age1=kid","data.age1=adult"),
default="none"))
rules_1_sorted <- sort(rules_1,by="confidence")
inspect(rules_1_sorted)

//visual

install.packages("arulesViz")
library(arulesViz)
plot(rules.all)
plot(rules.all, method = "grouped")

#Regression analysis

data2 <- read.csv("C:/Users/dprnj/OneDrive/문서/KYK/Rworks/StatwithR/ch1/Data/titanic_full_2.csv", header=T, na.strings=c("."))
str(data2)
data2<-na.omit(data2)
plot(data2$sex,data2$survived)
cor(data2)
result1<-lm(data2$survived~data2$sex+data2$age+data2$fare,data=data2)
summary(result1)`