在调整xgboost参数时，循环不在R中按预期工作

Question

此问题基于：

xgboost in R: how does xgb.cv pass the optimal parameters into xgb.train

我试图用不同的参数循环：

for (iter in 1:100){

param <- list(objective = "binary:logistic",
              eval_metric = "auc",
              max_depth = sample(2:6,1),
              eta = runif(.01,.1,.05),
              gamma = runif(.01,.05,.1), 
              subsample = runif(.9,.8,.7),
              colsample_bytree = runif(.8,.9,.5), 
              min_child_weight = sample(30:100,1),
              max_delta_step = sample(1:10,1)
)

但它抛出错误，因为param在第一次迭代时将值视为：

max_depth : int 6
eta : num(0)
gamma: num(0)
subsample : num(0)
colsample_bytree : num(0)
min_child_weight: int 63
max_delta_step: int 2

可能导致此行为的原因是什么？

Answer 1

好像我的runif函数错了。

这似乎有效：

param <- list(objective = "binary:logistic",
              eval_metric = "auc",
              max_depth = sample(2:6,1),
              eta = runif(1,.01,.05),
              gamma = runif(1,.01,.1), 
              subsample = runif(1,0.6,0.9),
              colsample_bytree = runif(1,.5,1), 
              min_child_weight = sample(30:100,1),
              max_delta_step = sample(1:10,1)