xgboost_train: Train xgboost model

In stackgbm: Stacked Gradient Boosting Machines

Train xgboost model

Description

Train xgboost model

Usage

xgboost_train(params, data, nrounds, ...)

Arguments

params	A list of parameters.
data	Training data.
nrounds	The Maximum number of boosting iterations.
...	Additional parameters.

Value

A model object.

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

stackgbm documentation built on May 29, 2024, 3:55 a.m.