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")
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