cv.folds>时,R gbm函数出错0 [英] Error in R gbm function when cv.folds > 0
问题描述
我正在使用gbm预测二进制响应.
当我设置cv.folds = 0时,一切正常.但是,当cv.folds> 1时,当交叉验证的第一个刺激完成时,出现错误:Error in object$var.levels[[i]] : subscript out of bounds
.有人说这可能是因为某些因子变量在训练或测试数据中缺少水平,但是我尝试仅使用数字变量仍然会出现此错误.
I am using gbm to predict binary response.
When I set cv.folds=0, everything works well. However when cv.folds > 1, I got error:Error in object$var.levels[[i]] : subscript out of bounds
when the first irritation of crossvalidation finished. Someone said this could because some factor variables have missing levels in training or testing data, but I tried only use numeric variables and still get this error.
> gbm.fit <- gbm(model.formula,
+ data=dataall_train,
+ distribution = "adaboost",
+ n.trees=10,
+ shrinkage=0.05,
+ interaction.depth=2,
+ bag.fraction = 0.5,
+ n.minobsinnode = 10,
+ train.fraction=0.5,
+ cv.folds=3,
+ verbose=T,
+ n.cores=1)
CV: 1
CV: 2
CV: 3
Error in object$var.levels[[i]] : subscript out of bounds
有人对此有见解吗?谢谢!
Anyone have some insights on this? Thanks!
回答我的自我: 问题解决了.这是因为此功能存在错误.输入数据中不能包含模型中的变量以外的其他变量.
Answer my self: Problem solved. This is because a bug in this function. The input data cannot contain variables other than the variables in the model.
推荐答案
我第二个解决方案:R函数 gbm()中的输入数据不能包含不会被包含的变量(列).在模型中使用.
I second this solution: The input data in the R function gbm() cannot include the variables (columns) that will not be used in your model.
这篇关于cv.folds>时,R gbm函数出错0的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!