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"randomForest.formula" <-
function(formula, data = NULL, ..., subset, na.action = na.fail) {
### formula interface for randomForest.
### code gratefully stolen from svm.formula (package e1071).
###
if (!inherits(formula, "formula"))
stop("method is only for formula objects")
m <- match.call(expand.dots = FALSE)
## Catch xtest and ytest in arguments.
if (any(c("xtest", "ytest") %in% names(m)))
stop("xtest/ytest not supported through the formula interface")
names(m)[2] <- "formula"
if (is.matrix(eval(m$data, parent.frame())))
m$data <- as.data.frame(data)
m$... <- NULL
m$na.action <- na.action
m[[1]] <- as.name("model.frame")
m <- eval(m, parent.frame())
#rn <- 1:nrow(m)
y <- model.response(m)
Terms <- attr(m, "terms")
attr(Terms, "intercept") <- 0
attr(y, "na.action") <- attr(m, "na.action")
## Drop any "negative" terms in the formula.
## test with:
## randomForest(Fertility~.-Catholic+I(Catholic<50),data=swiss,mtry=2)
m <- model.frame(terms(reformulate(attributes(Terms)$term.labels)),
data.frame(m))
## if (!is.null(y)) m <- m[, -1, drop=FALSE]
for (i in seq(along=m)) {
if (is.ordered(m[[i]])) m[[i]] <- as.numeric(m[[i]])
}
ret <- randomForest.default(m, y, ...)
cl <- match.call()
cl[[1]] <- as.name("randomForest")
ret$call <- cl
ret$terms <- Terms
if (!is.null(attr(y, "na.action"))) {
attr(ret$predicted, "na.action") <- ret$na.action <- attr(y, "na.action")
}
class(ret) <- c("randomForest.formula", "randomForest")
return(ret)
}
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