I am using the ranger package in caret to develop a random forest model to predict the risk of dying.

I am more interested in the model doing well at predicting those who end up dying, rather than being good at predicting those who live.

Therefore, I am trying to add a case.weights statement to my model, but I am dumbfounded as to how to to implement it, as I am very new to R.

So far, my code looks like this:

```
set.seed(40)
control.data <- trainControl(method= "cv", numer=5, sampling ="up", verboseIter = TRUE, classProbs = TRUE)
rfGrid <- expand.grid(
.mtry = 2:6,
.splitrule = "gini",
.min.node.size = c(250,500))
fit.dataup <- train(mort_30 ~ C_SEX+V_AGE+Hemoglobin,Thrombocytes+Leukocytes+CRP,
data = data.train,
method = "ranger",
max.depth = 5,
num.trees= 1000,
trControl = control.data,
tuneGrid = rfGrid,
importance = "impurity",
verbose = TRUE)
```

I have tried using both 'case.weights' and 'weights' in my train(), but no matter how I write it up, I cant get it to work.

Which syntax do I have to use? Let's say I want the "dead" cases to be weighted 2:1 to my "alive cases".

Thank you so much in advance!