在 xgboost R 包中, booster 给出了两个目标gbtree。
reg:logisticbinary:logistic
请参阅第 22 页(前 2 行)https://cran.r-project.org/web/packages/xgboost/xgboost.pdf
我想知道,这两种方法有什么区别?
在 xgboost R 包中, booster 给出了两个目标gbtree。
reg:logisticbinary:logistic请参阅第 22 页(前 2 行)https://cran.r-project.org/web/packages/xgboost/xgboost.pdf
我想知道,这两种方法有什么区别?
binary:logistic用于二进制分类,其中目标变量采用二进制输出[0, 1]
reg:logistic用于目标变量在 [0, 1] 之间连续的回归
引用 xgboost 文档:
We use linear regression here, if we want use objective = reg:logistic logistic regression, the label needed to be pre-scaled into [0,1]