Error : The tuning parameter grid should have columns mtry, SVM Regression

Question

我正在尝试使用 caret 包调整 SVM 回归模型。代码下方：

control <- trainControl(method="cv", number=5)
tunegrid <- expand.grid(.mtry=c(6:12), .ntree=c(500, 600, 700, 800, 900, 1000))
set.seed(2)
custom <- train(CRTOT_03~., data=train, method="rf", metric="rmse", tuneGrid=tunegrid, trControl=control)
summary(custom)
plot(custom)

我收到错误

Error : The tuning parameter grid should have columns mtry

Answer 1

您使用的是随机森林，而不是支持向量机。您收到错误消息，因为您只能在 caret 中随机森林的调整网格中设置 .mtry ntree 参数是通过将 ntree 传递给 train，例如

control <- trainControl(method="cv", number=5)
tunegrid <- expand.grid(.mtry = 6:12)
set.seed(2)
custom <- train(CRTOT_03~., 
          data=train, method="rf", 
          metric="rmse", 
          tuneGrid=tunegrid, 
          ntree = 1000,
          trControl=control)

ntree直接传递给randomForest

Error : The tuning parameter grid should have columns mtry, SVM Regression

Error : The tuning parameter grid should have columns mtry, SVM Regression

regression

r

svm

r-caret