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Unverified Commit b4213e96 authored by James Lamb's avatar James Lamb Committed by GitHub
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[R-package] fix warnings in examples (#4568) 

* [R-package] fix warnings in examples

* fix silently-ignored parameter
parent ee5636f1
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Showing with 130 additions and 64 deletions
R-package/R/lgb.Booster.R
View file @ b4213e96
...@@ -743,20 +743,23 @@ Booster <- R6::R6Class( ...@@ -743,20 +743,23 @@ Booster <- R6::R6Class(
#' data(agaricus.test, package = "lightgbm") #' data(agaricus.test, package = "lightgbm")
#' test <- agaricus.test #' test <- agaricus.test
#' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) #' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
#' params <- list(objective = "regression", metric = "l2") #' params <- list(
#' objective = "regression"
#' , metric = "l2"
#' , min_data = 1L
#' , learning_rate = 1.0
#' )
#' valids <- list(test = dtest) #' valids <- list(test = dtest)
#' model <- lgb.train( #' model <- lgb.train(
#' params = params #' params = params
#' , data = dtrain #' , data = dtrain
#' , nrounds = 5L #' , nrounds = 5L
#' , valids = valids #' , valids = valids
#' , min_data = 1L
#' , learning_rate = 1.0
#' ) #' )
#' preds <- predict(model, test$data) #' preds <- predict(model, test$data)
#' #'
#' # pass other prediction parameters #' # pass other prediction parameters
#' predict( #' preds <- predict(
#' model, #' model,
#' test$data, #' test$data,
#' params = list( #' params = list(
...@@ -824,15 +827,18 @@ predict.lgb.Booster <- function(object, ...@@ -824,15 +827,18 @@ predict.lgb.Booster <- function(object,
#' data(agaricus.test, package = "lightgbm") #' data(agaricus.test, package = "lightgbm")
#' test <- agaricus.test #' test <- agaricus.test
#' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) #' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
#' params <- list(objective = "regression", metric = "l2") #' params <- list(
#' objective = "regression"
#' , metric = "l2"
#' , min_data = 1L
#' , learning_rate = 1.0
#' )
#' valids <- list(test = dtest) #' valids <- list(test = dtest)
#' model <- lgb.train( #' model <- lgb.train(
#' params = params #' params = params
#' , data = dtrain #' , data = dtrain
#' , nrounds = 5L #' , nrounds = 5L
#' , valids = valids #' , valids = valids
#' , min_data = 1L
#' , learning_rate = 1.0
#' , early_stopping_rounds = 3L #' , early_stopping_rounds = 3L
#' ) #' )
#' model_file <- tempfile(fileext = ".txt") #' model_file <- tempfile(fileext = ".txt")
...@@ -885,15 +891,18 @@ lgb.load <- function(filename = NULL, model_str = NULL) { ...@@ -885,15 +891,18 @@ lgb.load <- function(filename = NULL, model_str = NULL) {
#' data(agaricus.test, package = "lightgbm") #' data(agaricus.test, package = "lightgbm")
#' test <- agaricus.test #' test <- agaricus.test
#' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) #' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
#' params <- list(objective = "regression", metric = "l2") #' params <- list(
#' objective = "regression"
#' , metric = "l2"
#' , min_data = 1L
#' , learning_rate = 1.0
#' )
#' valids <- list(test = dtest) #' valids <- list(test = dtest)
#' model <- lgb.train( #' model <- lgb.train(
#' params = params #' params = params
#' , data = dtrain #' , data = dtrain
#' , nrounds = 10L #' , nrounds = 10L
#' , valids = valids #' , valids = valids
#' , min_data = 1L
#' , learning_rate = 1.0
#' , early_stopping_rounds = 5L #' , early_stopping_rounds = 5L
#' ) #' )
#' lgb.save(model, tempfile(fileext = ".txt")) #' lgb.save(model, tempfile(fileext = ".txt"))
...@@ -936,15 +945,18 @@ lgb.save <- function(booster, filename, num_iteration = NULL) { ...@@ -936,15 +945,18 @@ lgb.save <- function(booster, filename, num_iteration = NULL) {
#' data(agaricus.test, package = "lightgbm") #' data(agaricus.test, package = "lightgbm")
#' test <- agaricus.test #' test <- agaricus.test
#' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) #' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
#' params <- list(objective = "regression", metric = "l2") #' params <- list(
#' objective = "regression"
#' , metric = "l2"
#' , min_data = 1L
#' , learning_rate = 1.0
#' )
#' valids <- list(test = dtest) #' valids <- list(test = dtest)
#' model <- lgb.train( #' model <- lgb.train(
#' params = params #' params = params
#' , data = dtrain #' , data = dtrain
#' , nrounds = 10L #' , nrounds = 10L
#' , valids = valids #' , valids = valids
#' , min_data = 1L
#' , learning_rate = 1.0
#' , early_stopping_rounds = 5L #' , early_stopping_rounds = 5L
#' ) #' )
#' json_model <- lgb.dump(model) #' json_model <- lgb.dump(model)
...@@ -983,15 +995,18 @@ lgb.dump <- function(booster, num_iteration = NULL) { ...@@ -983,15 +995,18 @@ lgb.dump <- function(booster, num_iteration = NULL) {
#' data(agaricus.test, package = "lightgbm") #' data(agaricus.test, package = "lightgbm")
#' test <- agaricus.test #' test <- agaricus.test
#' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) #' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
#' params <- list(objective = "regression", metric = "l2") #' params <- list(
#' objective = "regression"
#' , metric = "l2"
#' , min_data = 1L
#' , learning_rate = 1.0
#' )
#' valids <- list(test = dtest) #' valids <- list(test = dtest)
#' model <- lgb.train( #' model <- lgb.train(
#' params = params #' params = params
#' , data = dtrain #' , data = dtrain
#' , nrounds = 5L #' , nrounds = 5L
#' , valids = valids #' , valids = valids
#' , min_data = 1L
#' , learning_rate = 1.0
#' ) #' )
#' #'
#' # Examine valid data_name values #' # Examine valid data_name values
......
R-package/R/lgb.Dataset.R
View file @ b4213e96
...@@ -1145,12 +1145,15 @@ lgb.Dataset.set.categorical <- function(dataset, categorical_feature) { ...@@ -1145,12 +1145,15 @@ lgb.Dataset.set.categorical <- function(dataset, categorical_feature) {
#' #'
#' @examples #' @examples
#' \donttest{ #' \donttest{
#' # create training Dataset
#' data(agaricus.train, package ="lightgbm") #' data(agaricus.train, package ="lightgbm")
#' train <- agaricus.train #' train <- agaricus.train
#' dtrain <- lgb.Dataset(train$data, label = train$label) #' dtrain <- lgb.Dataset(train$data, label = train$label)
#'
#' # create a validation Dataset, using dtrain as a reference
#' data(agaricus.test, package = "lightgbm") #' data(agaricus.test, package = "lightgbm")
#' test <- agaricus.test #' test <- agaricus.test
#' dtest <- lgb.Dataset(test$data, test = train$label) #' dtest <- lgb.Dataset(test$data, label = test$label)
#' lgb.Dataset.set.reference(dtest, dtrain) #' lgb.Dataset.set.reference(dtest, dtrain)
#' } #' }
#' @rdname lgb.Dataset.set.reference #' @rdname lgb.Dataset.set.reference
......
R-package/R/lgb.cv.R
View file @ b4213e96
...@@ -63,14 +63,17 @@ CVBooster <- R6::R6Class( ...@@ -63,14 +63,17 @@ CVBooster <- R6::R6Class(
#' data(agaricus.train, package = "lightgbm") #' data(agaricus.train, package = "lightgbm")
#' train <- agaricus.train #' train <- agaricus.train
#' dtrain <- lgb.Dataset(train$data, label = train$label) #' dtrain <- lgb.Dataset(train$data, label = train$label)
#' params <- list(objective = "regression", metric = "l2") #' params <- list(
#' objective = "regression"
#' , metric = "l2"
#' , min_data = 1L
#' , learning_rate = 1.0
#' )
#' model <- lgb.cv( #' model <- lgb.cv(
#' params = params #' params = params
#' , data = dtrain #' , data = dtrain
#' , nrounds = 5L #' , nrounds = 5L
#' , nfold = 3L #' , nfold = 3L
#' , min_data = 1L
#' , learning_rate = 1.0
#' ) #' )
#' } #' }
#' @importFrom data.table data.table setorderv #' @importFrom data.table data.table setorderv
......
R-package/R/lgb.train.R
View file @ b4213e96
...@@ -36,15 +36,18 @@ ...@@ -36,15 +36,18 @@
#' data(agaricus.test, package = "lightgbm") #' data(agaricus.test, package = "lightgbm")
#' test <- agaricus.test #' test <- agaricus.test
#' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) #' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
#' params <- list(objective = "regression", metric = "l2") #' params <- list(
#' objective = "regression"
#' , metric = "l2"
#' , min_data = 1L
#' , learning_rate = 1.0
#' )
#' valids <- list(test = dtest) #' valids <- list(test = dtest)
#' model <- lgb.train( #' model <- lgb.train(
#' params = params #' params = params
#' , data = dtrain #' , data = dtrain
#' , nrounds = 5L #' , nrounds = 5L
#' , valids = valids #' , valids = valids
#' , min_data = 1L
#' , learning_rate = 1.0
#' , early_stopping_rounds = 3L #' , early_stopping_rounds = 3L
#' ) #' )
#' } #' }
......
R-package/R/lgb.unloader.R
View file @ b4213e96
...@@ -21,15 +21,18 @@ ...@@ -21,15 +21,18 @@
#' data(agaricus.test, package = "lightgbm") #' data(agaricus.test, package = "lightgbm")
#' test <- agaricus.test #' test <- agaricus.test
#' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) #' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
#' params <- list(objective = "regression", metric = "l2") #' params <- list(
#' objective = "regression"
#' , metric = "l2"
#' , min_data = 1L
#' , learning_rate = 1.0
#' )
#' valids <- list(test = dtest) #' valids <- list(test = dtest)
#' model <- lgb.train( #' model <- lgb.train(
#' params = params #' params = params
#' , data = dtrain #' , data = dtrain
#' , nrounds = 5L #' , nrounds = 5L
#' , valids = valids #' , valids = valids
#' , min_data = 1L
#' , learning_rate = 1.0
#' ) #' )
#' #'
#' lgb.unloader(restore = FALSE, wipe = FALSE, envir = .GlobalEnv) #' lgb.unloader(restore = FALSE, wipe = FALSE, envir = .GlobalEnv)
......
R-package/R/readRDS.lgb.Booster.R
View file @ b4213e96
...@@ -15,15 +15,18 @@ ...@@ -15,15 +15,18 @@
#' data(agaricus.test, package = "lightgbm") #' data(agaricus.test, package = "lightgbm")
#' test <- agaricus.test #' test <- agaricus.test
#' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) #' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
#' params <- list(objective = "regression", metric = "l2") #' params <- list(
#' objective = "regression"
#' , metric = "l2"
#' , min_data = 1L
#' , learning_rate = 1.0
#' )
#' valids <- list(test = dtest) #' valids <- list(test = dtest)
#' model <- lgb.train( #' model <- lgb.train(
#' params = params #' params = params
#' , data = dtrain #' , data = dtrain
#' , nrounds = 10L #' , nrounds = 10L
#' , valids = valids #' , valids = valids
#' , min_data = 1L
#' , learning_rate = 1.0
#' , early_stopping_rounds = 5L #' , early_stopping_rounds = 5L
#' ) #' )
#' model_file <- tempfile(fileext = ".rds") #' model_file <- tempfile(fileext = ".rds")
......
R-package/R/saveRDS.lgb.Booster.R
View file @ b4213e96
...@@ -26,15 +26,18 @@ ...@@ -26,15 +26,18 @@
#' data(agaricus.test, package = "lightgbm") #' data(agaricus.test, package = "lightgbm")
#' test <- agaricus.test #' test <- agaricus.test
#' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) #' dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
#' params <- list(objective = "regression", metric = "l2") #' params <- list(
#' objective = "regression"
#' , metric = "l2"
#' , min_data = 1L
#' , learning_rate = 1.0
#' )
#' valids <- list(test = dtest) #' valids <- list(test = dtest)
#' model <- lgb.train( #' model <- lgb.train(
#' params = params #' params = params
#' , data = dtrain #' , data = dtrain
#' , nrounds = 10L #' , nrounds = 10L
#' , valids = valids #' , valids = valids
#' , min_data = 1L
#' , learning_rate = 1.0
#' , early_stopping_rounds = 5L #' , early_stopping_rounds = 5L
#' ) #' )
#' model_file <- tempfile(fileext = ".rds") #' model_file <- tempfile(fileext = ".rds")
......
R-package/man/lgb.Dataset.set.reference.Rd
View file @ b4213e96
...@@ -19,12 +19,15 @@ If you want to use validation data, you should set reference to training data ...@@ -19,12 +19,15 @@ If you want to use validation data, you should set reference to training data
} }
\examples{ \examples{
\donttest{ \donttest{
# create training Dataset
data(agaricus.train, package ="lightgbm") data(agaricus.train, package ="lightgbm")
train <- agaricus.train train <- agaricus.train
dtrain <- lgb.Dataset(train$data, label = train$label) dtrain <- lgb.Dataset(train$data, label = train$label)
# create a validation Dataset, using dtrain as a reference
data(agaricus.test, package = "lightgbm") data(agaricus.test, package = "lightgbm")
test <- agaricus.test test <- agaricus.test
dtest <- lgb.Dataset(test$data, test = train$label) dtest <- lgb.Dataset(test$data, label = test$label)
lgb.Dataset.set.reference(dtest, dtrain) lgb.Dataset.set.reference(dtest, dtrain)
} }
} }
R-package/man/lgb.cv.Rd
View file @ b4213e96
...@@ -159,14 +159,17 @@ Cross validation logic used by LightGBM ...@@ -159,14 +159,17 @@ Cross validation logic used by LightGBM
data(agaricus.train, package = "lightgbm") data(agaricus.train, package = "lightgbm")
train <- agaricus.train train <- agaricus.train
dtrain <- lgb.Dataset(train$data, label = train$label) dtrain <- lgb.Dataset(train$data, label = train$label)
params <- list(objective = "regression", metric = "l2") params <- list(
objective = "regression"
, metric = "l2"
, min_data = 1L
, learning_rate = 1.0
)
model <- lgb.cv( model <- lgb.cv(
params = params params = params
, data = dtrain , data = dtrain
, nrounds = 5L , nrounds = 5L
, nfold = 3L , nfold = 3L
, min_data = 1L
, learning_rate = 1.0
) )
} }
} }
R-package/man/lgb.dump.Rd
View file @ b4213e96
...@@ -26,15 +26,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label) ...@@ -26,15 +26,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label)
data(agaricus.test, package = "lightgbm") data(agaricus.test, package = "lightgbm")
test <- agaricus.test test <- agaricus.test
dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
params <- list(objective = "regression", metric = "l2") params <- list(
objective = "regression"
, metric = "l2"
, min_data = 1L
, learning_rate = 1.0
)
valids <- list(test = dtest) valids <- list(test = dtest)
model <- lgb.train( model <- lgb.train(
params = params params = params
, data = dtrain , data = dtrain
, nrounds = 10L , nrounds = 10L
, valids = valids , valids = valids
, min_data = 1L
, learning_rate = 1.0
, early_stopping_rounds = 5L , early_stopping_rounds = 5L
) )
json_model <- lgb.dump(model) json_model <- lgb.dump(model)
......
R-package/man/lgb.get.eval.result.Rd
View file @ b4213e96
...@@ -40,15 +40,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label) ...@@ -40,15 +40,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label)
data(agaricus.test, package = "lightgbm") data(agaricus.test, package = "lightgbm")
test <- agaricus.test test <- agaricus.test
dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
params <- list(objective = "regression", metric = "l2") params <- list(
objective = "regression"
, metric = "l2"
, min_data = 1L
, learning_rate = 1.0
)
valids <- list(test = dtest) valids <- list(test = dtest)
model <- lgb.train( model <- lgb.train(
params = params params = params
, data = dtrain , data = dtrain
, nrounds = 5L , nrounds = 5L
, valids = valids , valids = valids
, min_data = 1L
, learning_rate = 1.0
) )
# Examine valid data_name values # Examine valid data_name values
......
R-package/man/lgb.load.Rd
View file @ b4213e96
...@@ -26,15 +26,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label) ...@@ -26,15 +26,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label)
data(agaricus.test, package = "lightgbm") data(agaricus.test, package = "lightgbm")
test <- agaricus.test test <- agaricus.test
dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
params <- list(objective = "regression", metric = "l2") params <- list(
objective = "regression"
, metric = "l2"
, min_data = 1L
, learning_rate = 1.0
)
valids <- list(test = dtest) valids <- list(test = dtest)
model <- lgb.train( model <- lgb.train(
params = params params = params
, data = dtrain , data = dtrain
, nrounds = 5L , nrounds = 5L
, valids = valids , valids = valids
, min_data = 1L
, learning_rate = 1.0
, early_stopping_rounds = 3L , early_stopping_rounds = 3L
) )
model_file <- tempfile(fileext = ".txt") model_file <- tempfile(fileext = ".txt")
......
R-package/man/lgb.save.Rd
View file @ b4213e96
...@@ -28,15 +28,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label) ...@@ -28,15 +28,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label)
data(agaricus.test, package = "lightgbm") data(agaricus.test, package = "lightgbm")
test <- agaricus.test test <- agaricus.test
dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
params <- list(objective = "regression", metric = "l2") params <- list(
objective = "regression"
, metric = "l2"
, min_data = 1L
, learning_rate = 1.0
)
valids <- list(test = dtest) valids <- list(test = dtest)
model <- lgb.train( model <- lgb.train(
params = params params = params
, data = dtrain , data = dtrain
, nrounds = 10L , nrounds = 10L
, valids = valids , valids = valids
, min_data = 1L
, learning_rate = 1.0
, early_stopping_rounds = 5L , early_stopping_rounds = 5L
) )
lgb.save(model, tempfile(fileext = ".txt")) lgb.save(model, tempfile(fileext = ".txt"))
......
R-package/man/lgb.train.Rd
View file @ b4213e96
...@@ -144,15 +144,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label) ...@@ -144,15 +144,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label)
data(agaricus.test, package = "lightgbm") data(agaricus.test, package = "lightgbm")
test <- agaricus.test test <- agaricus.test
dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
params <- list(objective = "regression", metric = "l2") params <- list(
objective = "regression"
, metric = "l2"
, min_data = 1L
, learning_rate = 1.0
)
valids <- list(test = dtest) valids <- list(test = dtest)
model <- lgb.train( model <- lgb.train(
params = params params = params
, data = dtrain , data = dtrain
, nrounds = 5L , nrounds = 5L
, valids = valids , valids = valids
, min_data = 1L
, learning_rate = 1.0
, early_stopping_rounds = 3L , early_stopping_rounds = 3L
) )
} }
......
R-package/man/lgb.unloader.Rd
View file @ b4213e96
...@@ -33,15 +33,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label) ...@@ -33,15 +33,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label)
data(agaricus.test, package = "lightgbm") data(agaricus.test, package = "lightgbm")
test <- agaricus.test test <- agaricus.test
dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
params <- list(objective = "regression", metric = "l2") params <- list(
objective = "regression"
, metric = "l2"
, min_data = 1L
, learning_rate = 1.0
)
valids <- list(test = dtest) valids <- list(test = dtest)
model <- lgb.train( model <- lgb.train(
params = params params = params
, data = dtrain , data = dtrain
, nrounds = 5L , nrounds = 5L
, valids = valids , valids = valids
, min_data = 1L
, learning_rate = 1.0
) )
lgb.unloader(restore = FALSE, wipe = FALSE, envir = .GlobalEnv) lgb.unloader(restore = FALSE, wipe = FALSE, envir = .GlobalEnv)
......
R-package/man/predict.lgb.Booster.Rd
View file @ b4213e96
...@@ -74,20 +74,23 @@ dtrain <- lgb.Dataset(train$data, label = train$label) ...@@ -74,20 +74,23 @@ dtrain <- lgb.Dataset(train$data, label = train$label)
data(agaricus.test, package = "lightgbm") data(agaricus.test, package = "lightgbm")
test <- agaricus.test test <- agaricus.test
dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
params <- list(objective = "regression", metric = "l2") params <- list(
objective = "regression"
, metric = "l2"
, min_data = 1L
, learning_rate = 1.0
)
valids <- list(test = dtest) valids <- list(test = dtest)
model <- lgb.train( model <- lgb.train(
params = params params = params
, data = dtrain , data = dtrain
, nrounds = 5L , nrounds = 5L
, valids = valids , valids = valids
, min_data = 1L
, learning_rate = 1.0
) )
preds <- predict(model, test$data) preds <- predict(model, test$data)
# pass other prediction parameters # pass other prediction parameters
predict( preds <- predict(
model, model,
test$data, test$data,
params = list( params = list(
......
R-package/man/readRDS.lgb.Booster.Rd
View file @ b4213e96
...@@ -26,15 +26,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label) ...@@ -26,15 +26,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label)
data(agaricus.test, package = "lightgbm") data(agaricus.test, package = "lightgbm")
test <- agaricus.test test <- agaricus.test
dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
params <- list(objective = "regression", metric = "l2") params <- list(
objective = "regression"
, metric = "l2"
, min_data = 1L
, learning_rate = 1.0
)
valids <- list(test = dtest) valids <- list(test = dtest)
model <- lgb.train( model <- lgb.train(
params = params params = params
, data = dtrain , data = dtrain
, nrounds = 10L , nrounds = 10L
, valids = valids , valids = valids
, min_data = 1L
, learning_rate = 1.0
, early_stopping_rounds = 5L , early_stopping_rounds = 5L
) )
model_file <- tempfile(fileext = ".rds") model_file <- tempfile(fileext = ".rds")
......
R-package/man/saveRDS.lgb.Booster.Rd
View file @ b4213e96
...@@ -50,15 +50,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label) ...@@ -50,15 +50,18 @@ dtrain <- lgb.Dataset(train$data, label = train$label)
data(agaricus.test, package = "lightgbm") data(agaricus.test, package = "lightgbm")
test <- agaricus.test test <- agaricus.test
dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
params <- list(objective = "regression", metric = "l2") params <- list(
objective = "regression"
, metric = "l2"
, min_data = 1L
, learning_rate = 1.0
)
valids <- list(test = dtest) valids <- list(test = dtest)
model <- lgb.train( model <- lgb.train(
params = params params = params
, data = dtrain , data = dtrain
, nrounds = 10L , nrounds = 10L
, valids = valids , valids = valids
, min_data = 1L
, learning_rate = 1.0
, early_stopping_rounds = 5L , early_stopping_rounds = 5L
) )
model_file <- tempfile(fileext = ".rds") model_file <- tempfile(fileext = ".rds")
......
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