Reputation: 22546
I am trying to get the class probability of a binary classification of a randomForest. I am struggling to get the right syntax. I have tried to read the help file but I have not found the answer. Any ideas?
> str(training)
'data.frame': 160051 obs. of 5 variables:
$ repeater : Factor w/ 2 levels "FALSE","TRUE": 1 1 1 1 1 1 1 1 1 1 ...
$ offervalue : num 0.75 0.75 1.5 0.75 1.25 1.25 1 0.75 0.75 0.75 ...
$ has_bought_brand : Factor w/ 2 levels "FALSE","TRUE": 1 1 2 1 1 1 2 1 1 1 ...
$ has_bought_company : Factor w/ 2 levels "FALSE","TRUE": 1 1 2 1 2 2 2 2 1 1 ...
$ has_bought_category: Factor w/ 2 levels "FALSE","TRUE": 2 1 1 1 2 2 2 1 1 1 ...
> model <- randomForest(repeater ~ offervalue + has_bought_brand + has_bought_company + has_bought_category, training, ntree=50)
> testPrediction <- predict(model, testing)
> str(testPrediction)
Factor w/ 2 levels "FALSE","TRUE": 1 1 1 1 1 1 1 1 1 1 ...
- attr(*, "names")= chr [1:64020] "4" "5" "11" "12" ...
Upvotes: 1
Views: 3784
Reputation: 206546
First of all, when posting code, make sure it's reproducible; ideally we should be able to copy/paste it into our own R sessions to get the same error/problem as you. Post a str()
of a data.set does not help. Often you can find simple examples in the help pages of the functions involved. The following example comes from ?randomForest
set.seed(71)
iris.rf <- randomForest(Species ~ ., data=iris, importance=TRUE,
proximity=TRUE)
since class(iris.rf)==c("randomForest.formula", "randomForest")
, when you call predict(iris.rf)
, you're actually calling predict.randomForest()
. The help page for ?predict.randomForest
gives the documentation for all the various parameters including the type=
parameter. By default it just returns the predicted class, but you can return the predicted probabilities with type="prob"
)
predict(iris.rf, type="prob")
which returns
setosa versicolor virginica
1 1.000000000 0.000000000 0.000000000
2 1.000000000 0.000000000 0.000000000
3 1.000000000 0.000000000 0.000000000
4 1.000000000 0.000000000 0.000000000
# etc ....
Upvotes: 5