小编Pau*_*ulG的帖子

我正在尝试使用本机伪 Huber loss 来拟合 xgboost 模型reg:pseudohubererror。然而，它似乎不起作用，因为训练和测试错误都没有改善。它与 一起工作得很好reg:squarederror。我缺少什么？

代码：

library(xgboost)
n = 1000
X = cbind(runif(n,10,20), runif(n,0,10))
y = X %*% c(2,3) + rnorm(n,0,1)

train = xgb.DMatrix(data  = X[-n,],
                    label = y[-n])

test = xgb.DMatrix(data   = t(as.matrix(X[n,])),
                   label = y[n]) 

watchlist = list(train = train, test = test)

xbg_test = xgb.train(data = train, objective = "reg:pseudohubererror", eval_metric = "mae", watchlist = watchlist, gamma = 1, eta = 0.01, nrounds = 10000, early_stopping_rounds = 100)

结果：

[1] train-mae:44.372692 …