CODEWITHSUNDEEP
rrstudiorandom-forest
user7273726
user7273726

Reputation: 11

Random Forest not generating err.rate

I'm using randomforest to analyze a training set of 600 rows of 21 variables.

# Construct Random Forest Model
rfmodel <- randomForest(default ~ .,
                    data = train.df,
                    ntree = 500,
                    mtry = 4,
                    importance = TRUE,
                    LocalImp = TRUE,
                    replace = FALSE)
print(rfmodel)

This generates the following:

> rfmodel <- randomForest(default ~ .,
+ data = train.df,
+ ntree = 500,
+ mtry = 4,
+ importance = TRUE,
+ LocalImp = TRUE,
+ replace = FALSE)

> Warning message:
> In randomForest.default(m, y, ...) :
> The response has five or fewer unique values. Are you sure you want to do 
> regression?

 > print(rfmodel)

>Call:
 randomForest(formula = default ~ ., data = train.df, ntree = 500,      mtry = 4, importance = TRUE, LocalImp = TRUE, replace = FALSE) 
           Type of random forest: regression
                 Number of trees: 500
No. of variables tried at each split: 4

      Mean of squared residuals: 0.1577596
                % Var explained: 23.89

This is missing the confusion matrix for some reason. When I try to generate the err.rate, it gives me this:

head(rfmodel$err.rate)
NULL

Upvotes: 1

Views: 951

Answers (1)

G5W
G5W

Reputation: 37641

I think that you want to do classification, but default is being treated as a numeric variable. try class(train.df$default). If that is in fact a numeric variable, you will need to convert it to a factor before running RF.

Upvotes: 1

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