% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/lgb.importance.R
\name{lgb.importance}
\alias{lgb.importance}
\title{Compute feature importance in a model}
\usage{
lgb.importance(model, percentage = TRUE)
}
\arguments{
\item{model}{object of class \code{lgb.Booster}.}

\item{percentage}{whether to show importance in relative percentage.}
}
\value{
For a tree model, a \code{data.table} with the following columns:
\itemize{
  \item \code{Feature} Feature names in the model.
  \item \code{Gain} The total gain of this feature's splits.
  \item \code{Cover} The number of observation related to this feature.
  \item \code{Frequency} The number of times a feature splited in trees.
}
}
\description{
Creates a \code{data.table} of feature importances in a model.
}
\examples{

data(agaricus.train, package = 'lightgbm')
train <- agaricus.train
dtrain <- lgb.Dataset(train$data, label = train$label)

params = list(objective = "binary",
              learning_rate = 0.01, num_leaves = 63, max_depth = -1,
              min_data_in_leaf = 1, min_sum_hessian_in_leaf = 1)
              model <- lgb.train(params, dtrain, 20)
model <- lgb.train(params, dtrain, 20)

tree_imp1 <- lgb.importance(model, percentage = TRUE)
tree_imp2 <- lgb.importance(model, percentage = FALSE)

}

