lgb.get.eval.result.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/lgb.Booster.R
\name{lgb.get.eval.result}
\alias{lgb.get.eval.result}
\title{Get record evaluation result from booster}
\usage{
lgb.get.eval.result(
  booster,
  data_name,
  eval_name,
  iters = NULL,
  is_err = FALSE
)
}
\arguments{
\item{booster}{Object of class \code{lgb.Booster}}

\item{data_name}{Name of the dataset to return evaluation results for.}

\item{eval_name}{Name of the evaluation metric to return results for.}

\item{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.}

\item{is_err}{TRUE will return evaluation error instead}
}
\value{
numeric vector of evaluation result
}
\description{
Given a \code{lgb.Booster}, return evaluation results for a
             particular metric on a particular dataset.
}
\examples{
\donttest{
\dontshow{setLGBMthreads(2L)}
\dontshow{data.table::setDTthreads(1L)}
# 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")
}
}