grur_lgbm_imputer: grur_lgbm_imputer

In thierrygosselin/grur: Imputations of RADseq data

Description

imputations using Ligh Gradient Boosting Machine

Usage

grur_lgbm_imputer(
  boost.split = NULL,
  markers.df = NULL,
  data.gbm = NULL,
  boosting = "dart",
  objective = "multiclass",
  learning_rate = 0.1,
  feature_fraction = 0.9,
  bagging_fraction = 0.9,
  bagging_freq = 1,
  max_depth = -1,
  min_data_in_leaf = 20,
  num_leaves = 31,
  cpu.boost = parallel::detectCores()/2,
  early_stopping_rounds = 10,
  nrounds = 200,
  iteration.subsample = 2,
  pmm = 2
)

thierrygosselin/grur documentation built on Oct. 28, 2020, 5:48 p.m.