Print xgb.cv result

Prints formatted results of xgb.cv().

Usage

# S3 method for class 'xgb.cv.synchronous'
print(x, verbose = FALSE, ...)

Arguments

x

An xgb.cv.synchronous object.

verbose

Whether to print detailed data.

...

Passed to data.table.print().

Details

When not verbose, it would only print the evaluation results, including the best iteration (when available).

Examples

data(agaricus.train, package = "xgboost")

train <- agaricus.train
cv <- xgb.cv(
  data = xgb.DMatrix(train$data, label = train$label, nthread = 1),
  nfold = 5,
  nrounds = 2,
  params = xgb.params(
    max_depth = 2,
    nthread = 2,
    objective = "binary:logistic"
  )
)
#> [1]	train-logloss:0.482039±0.000741	test-logloss:0.482209±0.001673 
#> [2]	train-logloss:0.359304±0.000751	test-logloss:0.359445±0.001502 
print(cv)
#> ##### xgb.cv 5-folds
#>   iter train_logloss_mean train_logloss_std test_logloss_mean test_logloss_std
#>  <int>              <num>             <num>             <num>            <num>
#>      1          0.4820394      0.0007411453         0.4822088      0.001672725
#>      2          0.3593041      0.0007513172         0.3594447      0.001502428
print(cv, verbose = TRUE)
#> ##### xgb.cv 5-folds
#> call:
#>   xgb.cv(params = xgb.params(max_depth = 2, nthread = 2, objective = "binary:logistic"), 
#>     data = xgb.DMatrix(train$data, label = train$label, nthread = 1), 
#>     nrounds = 2, nfold = 5)
#> params (as set within xgb.cv):
#>   objective = "binary:logistic", nthread = "2", max_depth = "2", silent = "1"
#> evaluation_log:
#>   iter train_logloss_mean train_logloss_std test_logloss_mean test_logloss_std
#>  <int>              <num>             <num>             <num>            <num>
#>      1          0.4820394      0.0007411453         0.4822088      0.001672725
#>      2          0.3593041      0.0007513172         0.3594447      0.001502428