lgb.wrap.metric: LightGBM evaluation metric wrapper

In Laurae2/LauraeDS: Laurae's Data Science Package

Description

The wrapper works only if both the wrapper and the original evaluation metric are existing. Requires Matrix and lightgbm packages.

Usage

lgb.wrap.metric(f, name, higher_better = FALSE)

Arguments

f	Type: function. The function to wrap from LightGBM. Requires the following order of arguments for the function to work: preds, labels, and returns a single value.
name	Type: character. The evaluation metric name which is printed and used for LightGBM variables.
higher_better	Type: logical. Whether a higher value means it is better. Defaults to FALSE.

Value

The wrapping function.

Examples

# Note: this example unexpectedly fails when using pkgdown.

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

evalerror <- function(preds, labels) {
  return(mean(abs(preds - labels)))
}
evalerror_wrap <- lgb.wrap.metric(f = evalerror, "mae", FALSE)
params <- list(learning_rate = 1, min_data = 1, nthread = 1)

set.seed(1)
model <- lgb.cv(params,
                dtrain,
                2,
                nfold = 5,
                objective = "regression",
                eval = evalerror_wrap)

Laurae2/LauraeDS documentation built on May 29, 2019, 2:25 p.m.