diff --git a/doc/R-package/xgboostPresentation.md b/doc/R-package/xgboostPresentation.md index b68507eb08ec..5b9d63599500 100644 --- a/doc/R-package/xgboostPresentation.md +++ b/doc/R-package/xgboostPresentation.md @@ -407,7 +407,7 @@ Until now, all the learnings we have performed were based on boosting trees. **X ```r -bst <- xgb.train(data=dtrain, booster = "gblinear", max.depth=2, nthread = 2, nrounds=2, watchlist=watchlist, eval.metric = "error", eval.metric = "logloss", objective = "binary:logistic") +bst <- xgb.train(data=dtrain, booster = "gblinear", nthread = 2, nrounds=2, watchlist=watchlist, eval.metric = "error", eval.metric = "logloss", objective = "binary:logistic") ``` ``` @@ -493,19 +493,19 @@ xgb.dump(bst, with_stats = T) ``` ``` -## [1] "booster[0]" +## [1] "booster[0]" ## [2] "0:[f28<-1.00136e-05] yes=1,no=2,missing=1,gain=4000.53,cover=1628.25" -## [3] "1:[f55<-1.00136e-05] yes=3,no=4,missing=3,gain=1158.21,cover=924.5" -## [4] "3:leaf=1.71218,cover=812" -## [5] "4:leaf=-1.70044,cover=112.5" +## [3] "1:[f55<-1.00136e-05] yes=3,no=4,missing=3,gain=1158.21,cover=924.5" +## [4] "3:leaf=1.71218,cover=812" +## [5] "4:leaf=-1.70044,cover=112.5" ## [6] "2:[f108<-1.00136e-05] yes=5,no=6,missing=5,gain=198.174,cover=703.75" -## [7] "5:leaf=-1.94071,cover=690.5" -## [8] "6:leaf=1.85965,cover=13.25" -## [9] "booster[1]" +## [7] "5:leaf=-1.94071,cover=690.5" +## [8] "6:leaf=1.85965,cover=13.25" +## [9] "booster[1]" ## [10] "0:[f59<-1.00136e-05] yes=1,no=2,missing=1,gain=832.545,cover=788.852" -## [11] "1:[f28<-1.00136e-05] yes=3,no=4,missing=3,gain=569.725,cover=768.39" -## [12] "3:leaf=0.784718,cover=458.937" -## [13] "4:leaf=-0.96853,cover=309.453" +## [11] "1:[f28<-1.00136e-05] yes=3,no=4,missing=3,gain=569.725,cover=768.39" +## [12] "3:leaf=0.784718,cover=458.937" +## [13] "4:leaf=-0.96853,cover=309.453" ## [14] "2:leaf=-6.23624,cover=20.4624" ```