改变Caret在R中创建的图中显示的调整参数。

Question

我使用R中的Caret包，用R中的'xgbTree'方法训练一个模型。

绘制训练后的模型，如下图所示：调整参数即'eta'=0.2不是我想要的，因为在训练模型之前，我也在expand.grid中定义了eta=0.1作为调整参数，这是最好的调整。所以我想把图中的eta=0.2改为图中函数中eta=0.1的情况。请问我怎么能做到呢？谢谢您了。

set.seed(100)  # For reproducibility

xgb_trcontrol = trainControl(
method = "cv",
#repeats = 2,
number = 10,  
#search = 'random',
allowParallel = TRUE,
verboseIter = FALSE,
returnData = TRUE
)


xgbGrid <- expand.grid(nrounds = c(100,200,1000),  # this is n_estimators in the python code above
                   max_depth = c(6:8),
                   colsample_bytree = c(0.6,0.7),
                   ## The values below are default values in the sklearn-api. 
                   eta = c(0.1,0.2),
                   gamma=0,
                   min_child_weight = c(5:8),
                   subsample = c(0.6,0.7,0.8,0.9)
)


set.seed(0) 
xgb_model8 = train(
x, y_train,  
trControl = xgb_trcontrol,
tuneGrid = xgbGrid,
method = "xgbTree"
)

Answer 1

会发生的情况是，绘图设备在你的网格的所有数值上进行绘图，最后出现的是eta=0.2。例如，你可以这样保存你的绘图。

xgb_trcontrol = trainControl(method = "cv", number = 3,returnData = TRUE)

xgbGrid <- expand.grid(nrounds = c(100,200,1000),  
                   max_depth = c(6:8),
                   colsample_bytree = c(0.6,0.7), 
                   eta = c(0.1,0.2),
                   gamma=0,
                   min_child_weight = c(5:8),
                   subsample = c(0.6,0.7,0.8,0.9)
)

set.seed(0)

x = mtcars[,-1]
y_train = mtcars[,1]

xgb_model8 = train(
x, y_train,  
trControl = xgb_trcontrol,
tuneGrid = xgbGrid,
method = "xgbTree"
)

你可以这样保存你的绘图

pdf("plots.pdf")
plot(xgb_model8,metric="RMSE")
dev.off()

或者如果你想绘制一个特定的参数 比如 eta=0. 2 你还需要修改以下内容 colsample_bytree，否则就是参数太多。

library(ggplot2)

ggplot(subset(xgb_model8$results
,eta==0.1 & colsample_bytree==0.6),
aes(x=min_child_weight,y=RMSE,group=factor(subsample),col=factor(subsample))) + 
geom_line() + geom_point() + facet_grid(nrounds~max_depth)