Construct lgb.Dataset object from dense matrix, sparse matrix
or local file (that was created previously by saving an lgb.Dataset).
lgb.Dataset(data, params = list(), reference = NULL, colnames = NULL, categorical_feature = NULL, free_raw_data = TRUE, info = list(), ...)
| data | a |
|---|---|
| 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 |
constructed dataset
library(lightgbm) data(agaricus.train, package = "lightgbm") train <- agaricus.train dtrain <- lgb.Dataset(train$data, label = train$label) lgb.Dataset.save(dtrain, "lgb.Dataset.data") dtrain <- lgb.Dataset("lgb.Dataset.data") lgb.Dataset.construct(dtrain)