R-随机森林预测因预测变量中的NA而失败

问题描述

文档(如果我没看错的话)说，如果随机森林预测函数遇到某些观测值的NA预测因子，则会产生NA预测.

The documentation (If I'm reading it correctly) says that the random forest predict function produces NA predictions if it encounters NA predictors for certain observations.

但是，如果我尝试在预测变量中使用某些NA的数据集上使用预测函数[2688中有7个观察结果中的NA]，则会遇到以下错误情况，并且预测失败.

However, if I try to use the predict function on a dataset with some NA's in predictors [NA's in 7 observations out of 2688] I encounter the following error condition, and prediction fails.

如果可能的话，我想避免一些混乱的解决方法.

There is a slightly messy work-around that I would like to avoid if possible.

我在做/读错东西吗?它与"inherits from randomForest.formula"子句有什么关系吗?

Am I doing/reading something wrong? Does it have to do something with the "inherits from randomForest.formula" clause?

推荐答案

使用文档中的一些示例:

Using some examples from the documentation:

set.seed(1)
x <- data.frame(x1=gl(32, 5), x2=runif(160), y=rnorm(160))
rf1 <- randomForest(x[-3], x[[3]], ntree=10)
> inherits(rf1,"randomForest.formula")
[1] FALSE

> iris.rf <- randomForest(Species ~ ., data=iris, importance=TRUE,
                         proximity=TRUE)
> inherits(iris.rf,"randomForest.formula")
[1] TRUE

因此，您可能在未使用公式界面适合您的模型的情况下调用了randomForest.

So you probably called randomForest without using the formula interface to fit your model.

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