titanic {RMixtComp} | R Documentation |
Titanic data set
Description
The data set provides information on the passengers of Titanic.
Usage
data(titanic)
Format
A data.frame with 1309 individuals and 8 variables.
survived: 0 = No, 1 = Yes (factor)
pclass: ticket class 1st, 2nd, 3rd (factor)
sex: male or female (factor)
age: age in years
sibsp: number of siblings/spouses aboard the Titanic
parch: number of parents/children aboard the Titanic
fare: ticket price in pounds
embarked: port of Embarkation C = Cherbourg, Q = Queenstown, S = Southampton (factor)
Source
Titanic People Database, Encyclopedia Titanica, https://www.encyclopedia-titanica.org/titanic-survivors/
https://www.kaggle.com/c/titanic/data
See Also
Other data:
CanadianWeather
,
prostate
,
simData
Examples
data(titanic)
head(titanic)
## Use the MixtComp format
dat <- titanic
# refactor categorical data: survived, sex, embarked and pclass
dat$sex <- refactorCategorical(dat$sex, c("male", "female", NA), c(1, 2, "?"))
dat$embarked <- refactorCategorical(dat$embarked, c("C", "Q", "S", NA), c(1, 2, 3, "?"))
dat$survived <- refactorCategorical(dat$survived, c(0, 1, NA), c(1, 2, "?"))
dat$pclass <- refactorCategorical(dat$pclass, c("1st", "2nd", "3rd"), c(1, 2, 3))
# replace all NA by ?
dat[is.na(dat)] <- "?"
# create model
model <- list(
pclass = "Multinomial",
survived = "Multinomial",
sex = "Multinomial",
age = "Gaussian",
sibsp = "Poisson",
parch = "Poisson",
fare = "Gaussian",
embarked = "Multinomial"
)
# create algo
algo <- createAlgo()
# run clustering
resLearn <- mixtCompLearn(dat, model, algo, nClass = 2:15, criterion = "ICL", nRun = 3, nCore = 1)
summary(resLearn)
plot(resLearn)
## Use standard data.frame and R format because titanic contains only standard variables.
# mixtCompLearn in "basic" mode without model parameters and data as a data.frame.
# A Multinomial model is used for factor variables, a Poisson for integer
# and a Gaussian for numeric.
resLearn <- mixtCompLearn(titanic, nClass = 2:15, nRun = 3, nCore = 1)
# imputed model
getType(resLearn)
[Package RMixtComp version 4.1.4 Index]