随机森林不生成err.rate

Question

我使用的是randomforest来分析600行21个变量的训练集。

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

这生成以下内容：

> 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 

这缺少某种原因混淆矩阵。当我尝试生成err.rate，它给了我这样的：

头（rfmodel $ err.rate）
NULL

Answer 1

我认为，你想要做分类，但默认情况下是被视为一个数字变量。尝试class(train.df$default)。如果这实际上是一个数字变量，那么在运行RF之前，您需要将其转换为一个因子。