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 ) 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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