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Clarification in Titanic R code
Global digits option causes error when displaying model results
If we set
> options(digits=2)
early in the code for output reasons, we will later see an error when attempting to display our first model:
> glm.tune.1 <- train(Fate ~ Sex + Class + Age + Family + Embarked,
data = train.batch,
method = "glm",
metric = "ROC",
trControl = cv.ctrl)
> glm.tune.1
Generalized Linear Model
714 samples
11 predictor
2 classes: 'Perished', 'Survived'
No pre-processing
Resampling: Cross-Validated (10 fold, repeated 3 times)
Summary of sample sizes: 643, 642, 643, 642, 642, 643, ...
Resampling results
Error in prettyNum(.Internal(format(x, trim, digits, nsmall, width, 3L, :
invalid 'digits' argument
You can remedy this by setting
options(digits=4)
Additional typos
In code chunk:
train.keeps <- c("Fate", "Sex", "Boat.dibs", "Age", "Title",
"Class", "Deck", "Side", "Fare", "Fare.pp",
"Embarked", "Family")"Survived" should be added to the train.keeps assignment.
very minor type
This line:
Titanic.logit.1 <- glm(Fate ~ Sex + Class + Age + Family + Embarked + Fare,
data = train.batch, family=binomial("logit")
missing the second ")".
Box-plot generation inhibits later commands
If running the code linearly, this bit of code to make the 'Title" column a factor (so we can make a box-plot),
> df.train$Title <- factor(df.train$Title,
c("Capt","Col","Major","Sir","Lady","Rev",
"Dr","Don","Jonkheer","the Countess","Mrs",
"Ms","Mr","Mme","Mlle","Miss","Master"))
will later cause an error when trying to reassign the grouped titles:
> df.train$Title <- changeTitles(df.train,
c("Capt", "Col", "Don", "Dr",
"Jonkheer", "Lady", "Major",
"Rev", "Sir"),
"Noble")
In `[<-.factor`(`*tmp*`, which(data$Title == honorific), value = c(13L, :
invalid factor level, NA generated
Survived missing in df.train.munged
Looks like you may need to include Survived in df.train.munged. Getting this error:
training.rows <- createDataPartition(df.train.munged$Survived,
-
Error in createDataPartition(df.train.munged$Survived, p = 0.8, list = FALSE) :
p = 0.8, list = FALSE)
y must have at least 2 data points
colnames(df.train.munged)
[1] "Fate" "Sex" "Boat.dibs" "Age" "Title" "Class" "Deck"
[8] "Side" "Fare" "Fare.pp" "Embarked" "Family"
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