Creates a `data.table`

of feature importances in a model.

lgb.importance(model, percentage = TRUE)

model | object of class |
---|---|

percentage | whether to show importance in relative percentage. |

For a tree model, a `data.table`

with the following columns:

`Feature`

: Feature names in the model.`Gain`

: The total gain of this feature's splits.`Cover`

: The number of observation related to this feature.`Frequency`

: The number of times a feature splited in trees.

library(lightgbm) 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 = 63L , max_depth = -1L , min_data_in_leaf = 1L , min_sum_hessian_in_leaf = 1.0 ) model <- lgb.train(params, dtrain, 10L) tree_imp1 <- lgb.importance(model, percentage = TRUE) tree_imp2 <- lgb.importance(model, percentage = FALSE)