Does anyone know if the error being generated when trying to predict
test set data in the Easy Uplift Tree package is something fixable by
the user or is this a bug in the program making the package essentially
non-operable?
This is from the package documentation and fails on the last step of
applying the model to the test set:
install.packages("EasyUpliftTree")
library(EasyUpliftTree)
library(survival)
data(colon)
#APPEARS TO WORK
sample.data <- na.omit(colon[colon$rx != "Lev" & colon$etype == 2, ])
treat <- ifelse(sample.data$rx == "Lev+5FU", 1, 0)
y <- ifelse(sample.data$status == 0, 1, 0)
x <- sample.data[, c(4:9, 11:14)]
x$v1 <- factor(x$sex)
x$v2 <- factor(x$obstruct)
x$v3 <- factor(x$perfor)
x$v4 <- factor(x$adhere)
x$v5 <- factor(x$differ)
x$v6 <- factor(x$extent)
x$v7 <- factor(x$surg)
x$v8 <- factor(x$node4)
index <- 1:nrow(x)
train.index <- index[(index%%2 == 0)]
test.index <- index[index%%2 != 0]
y.train <- y[train.index]
x.train <- x[train.index, ]
treat.train <- treat[train.index]
y.test <- y[test.index]
x.test <- x[test.index, ]
treat.test <- treat[test.index]
uplift.tree <- buildUpliftTree(y.train, treat.train, x.train)
print(uplift.tree)
#FAILS
apply(1:nrow(x.test), function(i) classify(uplift.tree, x.test[i, ]))
#Error in match.fun(FUN) : argument "FUN" is missing, with no default