I cannot understand what is going wrong here.
data.train <- read.table("Assign2.WineComplete.csv",sep=",",header=T)
# Building decision tree
Train <- data.frame(residual.sugar=data.train$residual.sugar,
total.sulfur.dioxide=data.train$total.sulfur.dioxide,
alcohol=data.train$alcohol,
quality=data.train$quality)
Pre <- as.formula("pre ~ quality")
fit <- rpart(Pre, method="class",data=Train)
I am getting the following error :
Error in eval(expr, envir, enclos) : object 'pre' not found
Don't know why @Janos deleted his answer, but it's correct: your data frame Train
doesn't have a column named pre
. When you pass a formula and a data frame to a model-fitting function, the names in the formula have to refer to columns in the data frame. Your Train
has columns called residual.sugar
, total.sulfur
, alcohol
and quality
. You need to change either your formula or your data frame so they're consistent with each other.
And just to clarify: Pre
is an object containing a formula. That formula contains a reference to the variable pre
. It's the latter that has to be consistent with the data frame.