Contents
How does R handle factors?
Factors in R are stored as a vector of integer values with a corresponding set of character values to use when the factor is displayed. The factor function is used to create a factor. The only required argument to factor is a vector of values which will be returned as a vector of factor values.
What is a caret character?
The caret (/ˈkærɪt/) is a V-shaped grapheme, usually inverted and sometimes extended, used in proofreading and typography to indicate that additional material needs to be inserted at this point in the text. There is a similar mark, ^, that has a variety of uses in programming, mathematics and other contexts.
How are factor variables handled in the caret package?
Different methods have different handling of categorical predictors. Some methods cannot handle factor variables. Thankfully, the R community has essentially provided a silver bullet for these issues, the caret package. Returning to the above list, we will see that a number of these tasks are directly addressed in the caret package.
What are the arguments to the caret function?
Here, we have supplied four arguments to the train () function form the caret package. form = default ~ . specifies the default variable as the response. It also indicates that all available predictors should be used. trControl = trainControl (method = “cv”, number = 5) specifies that we will be using 5-fold cross-validation.
What happens when you use rpart with caret?
Rpart using Caret changes names of Factors. If I have a factor e.g. sexe with two levels MALE and FEMELLE let’s say, using rpart alone I get splits that say for example Sexe = Male and then a yes no split. However using rpart with caret I get a weird renaming of variables:
How is the default data used in caret?
To illustrate caret, first for classification, we will use the Default data from the ISLR package. We first test-train split the data using createDataPartition. Here we are using 75% of the data for training. At first glance, it might appear as if the use of createDataPartition () is no different than our previous use of sample ().