在随机森林mtry图中添加点

Question

我使用带有插入包的随机森林来设置最佳mtry（预测因子的数量）。当我绘制模型以查看RMSE与mtry的变化时，我想在最好的mtry中添加一个点

ctrl <- trainControl(method = "cv", savePred=T, number = 10)
tunegrid <- expand.grid(.mtry=seq(from=2,to=nlayers(covs_processed),by=2))
# Search for the best mtry parameter
rfmodel <- train(fm, data=dat_1963@data, method = "rf", trControl = ctrl,
                 importance=TRUE, tuneGrid=tunegrid)

plot(rfmodel,main= "Tuning RF 2018")

位置点：

rfmodel[11][[1]]$tuneValue[[1]]

24

min(rfmodel$results$RMSE)

2.972381

我尝试用这段代码添加点，但我可以

points(rfmodel[11][[1]]$tuneValue[[1]],min(rfmodel$results$RMSE),col="red")

该模型可以在这里找到：https://drive.google.com/open?id=1tFFgxuCiJNC4PLMekBG7bgEziKGwMJmu

Answer 1

plot()中的caret方法使用lattice包而不是基础图形，所以lines不起作用。

通过添加新的绘图图层，您可以使用ggplot方法轻松获得结果。这有两个选择：

library(caret)
#> Loading required package: lattice
#> Loading required package: ggplot2
data(BloodBrain)

theme_set(theme_bw())

ctrl <- trainControl(method = "cv", number = 10, returnResamp = "all")
set.seed(214)
rfmodel <-
  train(
    x = bbbDescr, y = logBBB,
    method = "rf",
    preProc = "zv",
    trControl = ctrl,
    tuneGrid = data.frame(mtry = 1:10)
  )

# rfmodel$resample contains the individual RMSE values per fold. Use the
# ggplot method and add another layer with those points. 

ggplot(rfmodel) + 
  geom_point(data = rfmodel$resample, alpha = .3)

# or add them as colored lines 
ggplot(rfmodel) + 
  geom_line(
    data = rfmodel$resample, 
    # For each resample, plot a different colored line
    aes(group = Resample, col = Resample),
    alpha = .3) + 
  # the legend here gets huge so stop it from being printed
  theme(legend.position = "none")

由reprex package创建于2019-04-03（v0.2.1）