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In xgboost R package, there are two objectives given with booster gbtree.
reg:logisticbinary:logisticSee,page 22 (first 2 lines) https://cran.r-project.org/web/packages/xgboost/xgboost.pdf
I was wondering, what is the difference between these two methods?
binary:logistic is used for binary classification where the target variable takes binary output [0, 1]
reg:logistic is used for regression where the target variable is continuous between [0, 1]
Quote from xgboost doc:
We use linear regression here, if we want use objective = reg:logistic logistic regression, the label needed to be pre-scaled into [0,1]
