How can I use result of `randomForest` call in **R** to predict labels on some unlabled data (e.g. real world input to be classified)?  

Code:

```
train_data = read.csv("train.csv")
input_data = read.csv("input.csv")
result_forest = randomForest(Label ~ ., data=train_data)
labeled_input = result_forest.predict(input_data) # I need something like this

```

train.csv:

```
a;b;c;label;
1;1;1;a;
2;2;2;b;
1;2;1;c;

```

input.csv:

```
a;b;c;
1;1;1;
2;1;2;

```

I need to get something like this

```
a;b;c;label;
1;1;1;a;
2;1;2;b;

```