Change SMOTE parameters inside CARET k-fold cross-validation classification - r

Question

I have a classification problem with a very skewed class to predict (e.g. 90% / 10% unbalanced binary variable to predict).
In order to deal with that issue, I want to use the SMOTE method to oversample this class variable. However, as I read here (http://www.marcoaltini.com/blog/dealing-with-imbalanced-data-undersampling-oversampling-and-proper-cross-validation) it is best practice to use SMOTE inside the k-fold loop to avoid overfitting.
As I'm using the caret package to perform my analysis, I'm referring to this link (http://topepo.github.io/caret/sampling.html). I undestand everything perfectly but the last part where it explains how to change the SMOTE parameters:
smotest <- list(name = "SMOTE with more neighbors!",
func = function (x, y) {
library(DMwR)
dat <- if (is.data.frame(x)) x else as.data.frame(x)
dat$.y <- y
dat <- SMOTE(.y ~ ., data = dat, k = 10)
list(x = dat[, !grepl(".y", colnames(dat), fixed = TRUE)],
y = dat$.y)
},
first = TRUE)
I simply don't understand this. Someone care to explain? Let's say I want to include the SMOTE parameters perc.over, k and perc.under, how would I do that?
Thank you very much.
EDIT:
Actually I realized I could probably just add these parameters inside the "SMOTE" expression in the above function, this would for instance give something like:
smotest <- list(name = "SMOTE with more neighbors!",
func = function (x, y) {
library(DMwR)
dat <- if (is.data.frame(x)) x else as.data.frame(x)
dat$.y <- y
dat <- SMOTE(.y ~ ., data = dat, k = 10, perc.over = 1200, perc.under = 100)
list(x = dat[, !grepl(".y", colnames(dat), fixed = TRUE)],
y = dat$.y)
},
first = TRUE)

Answer 1

I am not sure to have understood what you do not understand but here is an attempt to clarify what is done in this piece of code.
The smotest object is created as list because it is the way the argument sampling of trainControl function must be represented. The first element of this list is a name used only for display purposes. The second, func, is the actual sampling function. The third, first, is a logical value indicating whether samplin must be done before or after the pre-processing step.
The element func is here only a wrapper of SMOTE function. In this wrapper, line 3 is here because only a data.frame can be passed to SMOTE function. Line 4 is added because a formula combined to a data.frame is used in SMOTE rather than a couple x y. Line 6 is here to ensure that the appropriate format is returned to trainControl.
And, to answer you last question: yes, you can do what you have proposed to set additional parameters to SMOTE.