| lgb.get.eval.result | R Documentation | 
Given a lgb.Booster, return evaluation results for a
particular metric on a particular dataset.
lgb.get.eval.result(
  booster,
  data_name,
  eval_name,
  iters = NULL,
  is_err = FALSE
)
| booster | Object of class  | 
| data_name | Name of the dataset to return evaluation results for. | 
| eval_name | Name of the evaluation metric to return results for. | 
| iters | An integer vector of iterations you want to get evaluation results for. If NULL (the default), evaluation results for all iterations will be returned. | 
| is_err | TRUE will return evaluation error instead | 
numeric vector of evaluation result
# train a regression model
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"
  , min_data = 1L
  , learning_rate = 1.0
  , num_threads = 2L
)
valids <- list(test = dtest)
model <- lgb.train(
  params = params
  , data = dtrain
  , nrounds = 5L
  , valids = valids
)
# Examine valid data_name values
print(setdiff(names(model$record_evals), "start_iter"))
# Examine valid eval_name values for dataset "test"
print(names(model$record_evals[["test"]]))
# Get L2 values for "test" dataset
lgb.get.eval.result(model, "test", "l2")
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.