Summary method for the gbt function

# S3 method for gbt
summary(object, prn = TRUE, ...)

Arguments

object

Return value from gbt

prn

Print iteration history

...

further arguments passed to or from other methods

Details

See https://radiant-rstats.github.io/docs/model/gbt.html for an example in Radiant

See also

gbt to generate results

plot.gbt to plot results

predict.gbt for prediction

Examples

result <- gbt(titanic, "survived", c("pclass", "sex"), early_stopping_rounds = 0) %>% str()
#> List of 26 #> $ check : chr "" #> $ model :List of 15 #> ..$ handle :Class 'xgb.Booster.handle' <externalptr> #> ..$ raw : raw [1:3937] 43 4f 4e 46 ... #> ..$ best_iteration : num 1 #> ..$ best_ntreelimit: int 1 #> ..$ best_score : num 0.825 #> ..$ best_msg : chr "[1]\ttrain-auc:0.824504" #> ..$ niter : int 2 #> ..$ evaluation_log :Classes ‘data.table’ and 'data.frame': 2 obs. of 2 variables: #> .. ..$ iter : num [1:2] 1 2 #> .. ..$ train_auc: num [1:2] 0.825 0.825 #> .. ..- attr(*, ".internal.selfref")=<externalptr> #> ..$ call : language xgb.train(params = params, data = dtrain, nrounds = nrounds, watchlist = watchlist, verbose = verbose, print| __truncated__ ... #> ..$ params :List of 9 #> .. ..$ max_depth : num 6 #> .. ..$ learning_rate : num 0.3 #> .. ..$ min_split_loss : num 0 #> .. ..$ min_child_weight : num 1 #> .. ..$ subsample : num 1 #> .. ..$ nthread : num 12 #> .. ..$ objective : chr "binary:logistic" #> .. ..$ eval_metric : chr "auc" #> .. ..$ validate_parameters: logi TRUE #> ..$ callbacks :List of 3 #> .. ..$ cb.print.evaluation:function (env = parent.frame()) #> .. .. ..- attr(*, "call")= language cb.print.evaluation(period = print_every_n) #> .. .. ..- attr(*, "name")= chr "cb.print.evaluation" #> .. ..$ cb.evaluation.log :function (env = parent.frame(), finalize = FALSE) #> .. .. ..- attr(*, "call")= language cb.evaluation.log() #> .. .. ..- attr(*, "name")= chr "cb.evaluation.log" #> .. ..$ cb.early.stop :function (env = parent.frame(), finalize = FALSE) #> .. .. ..- attr(*, "call")= language cb.early.stop(stopping_rounds = early_stopping_rounds, maximize = maximize, verbose = verbose) #> .. .. ..- attr(*, "name")= chr "cb.early.stop" #> ..$ feature_names : chr [1:3] "pclass2nd" "pclass3rd" "sexmale" #> ..$ nfeatures : int 3 #> ..$ importance :Classes ‘data.table’ and 'data.frame': 3 obs. of 4 variables: #> .. ..$ Feature : chr [1:3] "sexmale" "pclass3rd" "pclass2nd" #> .. ..$ Gain : num [1:3] 0.758 0.21 0.032 #> .. ..$ Cover : num [1:3] 0.435 0.435 0.13 #> .. ..$ Frequency: num [1:3] 0.25 0.5 0.25 #> .. ..- attr(*, ".internal.selfref")=<externalptr> #> ..$ model : tibble [1,043 × 3] (S3: tbl_df/tbl/data.frame) #> .. ..$ survived: Factor w/ 2 levels "Yes","No": 1 1 2 2 2 1 1 2 1 2 ... #> .. ..$ pclass : Factor w/ 3 levels "1st","2nd","3rd": 1 1 1 1 1 1 1 1 1 1 ... #> .. ..$ sex : Factor w/ 2 levels "female","male": 1 2 1 2 1 2 1 2 1 2 ... #> .. ..- attr(*, "description")= chr "## Titanic\n\nThis dataset describes the survival status of individual passengers on the Titanic. The titanic d"| __truncated__ #> ..- attr(*, "class")= chr "xgb.Booster" #> $ output : chr [1:7] "[1]\ttrain-auc:0.824504 " "Will train until train_auc hasn't improved in 0 rounds." "" "[2]\ttrain-auc:0.824504 " ... #> $ check_args :function (arg, default, inp = gbt_input) #> $ extra_args_names : NULL #> $ extra_args : list() #> $ gbt_input :List of 10 #> ..$ max_depth : num 6 #> ..$ learning_rate : num 0.3 #> ..$ min_split_loss : num 0 #> ..$ nrounds : num 100 #> ..$ min_child_weight : num 1 #> ..$ subsample : num 1 #> ..$ early_stopping_rounds: num 0 #> ..$ nthread : num 12 #> ..$ objective : chr "binary:logistic" #> ..$ eval_metric : chr "auc" #> $ not_vary : chr(0) #> $ nr_obs : int 1043 #> $ df_name : chr "titanic" #> $ vars : chr [1:2] "pclass" "sex" #> $ rvar : chr "survived" #> $ evar : chr [1:2] "pclass" "sex" #> $ type : chr "classification" #> $ lev : chr "Yes" #> $ max_depth : num 6 #> $ learning_rate : num 0.3 #> $ min_split_loss : num 0 #> $ min_child_weight : num 1 #> $ subsample : num 1 #> $ nrounds : num 100 #> $ early_stopping_rounds: num 0 #> $ nthread : num 12 #> $ wts : NULL #> $ seed : chr NA #> $ data_filter : chr "" #> - attr(*, "class")= chr [1:3] "gbt" "model" "list"
summary(result)
#> Length Class Mode #> 0 NULL NULL