lightgbm: lgb.Dataset – R documentation

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lgb.Dataset

Construct lgb.Dataset object

Description

Construct lgb.Dataset object from dense matrix, sparse matrix or local file (that was created previously by saving an lgb.Dataset).

Usage

lgb.Dataset(
  data,
  params = list(),
  reference = NULL,
  colnames = NULL,
  categorical_feature = NULL,
  free_raw_data = TRUE,
  info = list(),
  ...
)

Arguments

`data`	a `matrix` object, a `dgCMatrix` object or a character representing a filename
`params`	a list of parameters
`reference`	reference dataset
`colnames`	names of columns
`categorical_feature`	categorical features
`free_raw_data`	TRUE for need to free raw data after construct
`info`	a list of information of the `lgb.Dataset` object
`...`	other information to pass to `info` or parameters pass to `params`

Value

constructed dataset

Examples

data(agaricus.train, package = "lightgbm")
train <- agaricus.train
dtrain <- lgb.Dataset(train$data, label = train$label)
data_file <- tempfile(fileext = ".data")
lgb.Dataset.save(dtrain, data_file)
dtrain <- lgb.Dataset(data_file)
lgb.Dataset.construct(dtrain)

lightgbm

Light Gradient Boosting Machine

v3.2.1

MIT + file LICENSE

Authors

Guolin Ke [aut, cre], Damien Soukhavong [aut], James Lamb [aut], Qi Meng [aut], Thomas Finley [aut], Taifeng Wang [aut], Wei Chen [aut], Weidong Ma [aut], Qiwei Ye [aut], Tie-Yan Liu [aut], Yachen Yan [ctb], Microsoft Corporation [cph], Dropbox, Inc. [cph], Jay Loden [cph], Dave Daeschler [cph], Giampaolo Rodola [cph], Alberto Ferreira [ctb], Daniel Lemire [ctb], Victor Zverovich [cph], IBM Corporation [ctb]

Initial release

2021-04-12