我想使用我的训练数据来训练随机森林模型，但是发生了一些错误 .
错误消息如下：
Error in train.default(x, y, weights = w, ...) :
At least one of the class levels is not a valid R variable name; This will cause errors when class probabilities
are generated because the variables names will be converted to X1, X2, X3, X4, X5, X6, X7 . Please use factor
levels that can be used as valid R variable names (see ?make.names for help).
以下是我的代码：
rf.ctrl <- trainControl(method = "repeatedcv",
number = 10,
repeats = 10,
classProbs = TRUE,
summaryFunction = twoClassSummary)
set.seed(256)
#train the calssification model with random forest
rf.model <- train(as.factor(response) ~ .,data = trainvals,
method = "rf",
trControl = rf.ctrl,
tuneLength = 10,
metic = "ROC")
trainvals的结构是：
类的响应级别是1,2,3,4,5,6和7 .
1 回答
trainvals数据框中的一个或多个列不是因子类型，因此会出现错误 . 您可以使用以下内容将所有列转换为factor：