Train xgboost model
Arguments
- params
A list of parameters.
- data
Training data.
- nrounds
The Maximum number of boosting iterations.
- ...
Additional parameters.
Examples
sim_data <- msaenet::msaenet.sim.binomial(
n = 100,
p = 10,
rho = 0.6,
coef = rnorm(5, mean = 0, sd = 10),
snr = 1,
p.train = 0.8,
seed = 42
)
x_train <- xgboost_dmatrix(sim_data$x.tr, label = sim_data$y.tr)
fit <- xgboost_train(
params = list(
objective = "binary:logistic",
eval_metric = "auc",
max_depth = 3,
eta = 0.1
),
data = x_train,
nrounds = 100,
nthread = 1
)
fit
#> ##### xgb.Booster
#> raw: 100.1 Kb
#> call:
#> xgboost::xgb.train(params = list(objective = "binary:logistic",
#> eval_metric = "auc", max_depth = 3, eta = 0.1), data = <pointer: 0x559fc8dc3390>,
#> nrounds = 100, nthread = 1)
#> params (as set within xgb.train):
#> objective = "binary:logistic", eval_metric = "auc", max_depth = "3", eta = "0.1", nthread = "1", validate_parameters = "TRUE"
#> xgb.attributes:
#> niter
#> callbacks:
#> cb.print.evaluation(period = print_every_n)
#> niter: 100
#> nfeatures : 10