Save LightGBM model

lgb.save(booster, filename, num_iteration = NULL)

Arguments

booster

Object of class lgb.Booster

filename

saved filename

num_iteration

number of iteration want to predict with, NULL or <= 0 means use best iteration

Value

lgb.Booster

Examples

library(lightgbm) data(agaricus.train, package = "lightgbm") train <- agaricus.train dtrain <- lgb.Dataset(train$data, label = train$label) data(agaricus.test, package = "lightgbm") test <- agaricus.test dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) params <- list(objective = "regression", metric = "l2") valids <- list(test = dtest) model <- lgb.train( params = params , data = dtrain , nrounds = 10L , valids = valids , min_data = 1L , learning_rate = 1.0 , early_stopping_rounds = 5L )
#> [1]: test's l2:6.44165e-17 #> [2]: test's l2:6.44165e-17 #> [3]: test's l2:6.44165e-17 #> [4]: test's l2:6.44165e-17 #> [5]: test's l2:6.44165e-17 #> [6]: test's l2:6.44165e-17 #> [7]: test's l2:6.44165e-17 #> [8]: test's l2:6.44165e-17
lgb.save(model, "model.txt")