Boosted trees with lightgbm — train

train_lightgbm is a wrapper for lightgbm tree-based models where all of the model arguments are in the main function.

Usage

train_lightgbm(
  x,
  y,
  weights = NULL,
  max_depth = -1,
  num_iterations = 100,
  learning_rate = 0.1,
  feature_fraction_bynode = 1,
  min_data_in_leaf = 20,
  min_gain_to_split = 0,
  bagging_fraction = 1,
  early_stopping_round = NULL,
  validation = 0,
  counts = TRUE,
  quiet = FALSE,
  ...
)

Arguments

x: A data frame or matrix of predictors
y: A vector (factor or numeric) or matrix (numeric) of outcome data.
weights: A numeric vector of sample weights.
max_depth: An integer for the maximum depth of the tree.
num_iterations: An integer for the number of boosting iterations.
learning_rate: A numeric value between zero and one to control the learning rate.
feature_fraction_bynode: Fraction of predictors that will be randomly sampled at each split.
min_data_in_leaf: A numeric value for the minimum sum of instances needed in a child to continue to split.
min_gain_to_split: A number for the minimum loss reduction required to make a further partition on a leaf node of the tree.
bagging_fraction: Subsampling proportion of rows. Setting this argument to a non-default value will also set bagging_freq = 1. See the Bagging section in ?details_boost_tree_lightgbm for more details.
early_stopping_round: Number of iterations without an improvement in the objective function occur before training should be halted.
validation: The proportion of the training data that are used for performance assessment and potential early stopping.
counts: A logical; should feature_fraction_bynode be interpreted as the number of predictors that will be randomly sampled at each split? TRUE indicates that mtry will be interpreted in its sense as a count, FALSE indicates that the argument will be interpreted in its sense as a proportion.
quiet: A logical; should logging by lightgbm::lgb.train() be muted?
...: Other options to pass to lightgbm::lgb.train(). Arguments will be correctly routed to the param argument, or as a main argument, depending on their name.

Value

A fitted lightgbm.Model object.

Details

This is an internal function, not meant to be directly called by the user.