Instalar paquetes y librerias

#install.packages("rpart")
library(rpart)
#install.packages("rpart.plot")
library(rpart.plot)

Importar la base de datos

titanic <- read.csv("C:\\Users\\corsa\\OneDrive - CORSA Transportes SA de CV\\Descargas\\titanic.csv")
titanic <- titanic[,c("pclass","age","sex","survived")]

Entender la base de datos

str(titanic)
## 'data.frame':    1310 obs. of  4 variables:
##  $ pclass  : int  1 1 1 1 1 1 1 1 1 1 ...
##  $ age     : num  29 0.917 2 30 25 ...
##  $ sex     : chr  "female" "male" "female" "male" ...
##  $ survived: int  1 1 0 0 0 1 1 0 1 0 ...

Crear arbol de decisiones

titanic <- titanic[,c("pclass","age","sex","survived")]
titanic$survived <- as.factor(titanic$survived)
titanic$pclass <- as.factor(titanic$pclass)
str(titanic)
## 'data.frame':    1310 obs. of  4 variables:
##  $ pclass  : Factor w/ 3 levels "1","2","3": 1 1 1 1 1 1 1 1 1 1 ...
##  $ age     : num  29 0.917 2 30 25 ...
##  $ sex     : chr  "female" "male" "female" "male" ...
##  $ survived: Factor w/ 2 levels "0","1": 2 2 1 1 1 2 2 1 2 1 ...
arbol_titanic <- rpart(survived~., data=titanic)
rpart.plot(arbol_titanic)

prp(arbol_titanic, extra=7, prefix="fracción\n")

Conclusion

En conclusion, la probabilidad más alta de sobrevivir el accidente es: * 100% = ser niño menor a 9.5 años de 1ra o 2da clase * 73% = ser mujer Y por otro lado, las probabilidades más bajas son: * 17% = ser un adulto hombre * 38% = ser niño menor a 9.5 años y ser de 3ra clase

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