Commit 62bae24b authored by Laurae's avatar Laurae Committed by Guolin Ke
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[R-package] Fix demos not using lgb.Dataset.create.valid (#1993)

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* Hand edit broken commit

* Hand edit broken commit

* Hand edit broken commit
parent 2c9d3320
...@@ -5,7 +5,7 @@ require(methods) ...@@ -5,7 +5,7 @@ require(methods)
data(agaricus.train, package = "lightgbm") data(agaricus.train, package = "lightgbm")
data(agaricus.test, package = "lightgbm") data(agaricus.test, package = "lightgbm")
dtrain <- lgb.Dataset(agaricus.train$data, label = agaricus.train$label) dtrain <- lgb.Dataset(agaricus.train$data, label = agaricus.train$label)
dtest <- lgb.Dataset(agaricus.test$data, label = agaricus.test$label) dtest <- lgb.Dataset.create.valid(dtrain, data = agaricus.test$data, label = agaricus.test$label)
valids <- list(eval = dtest, train = dtrain) valids <- list(eval = dtest, train = dtrain)
#--------------------Advanced features --------------------------- #--------------------Advanced features ---------------------------
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...@@ -70,8 +70,9 @@ my_data_test <- as.matrix(bank_test[, 1:16, with = FALSE]) ...@@ -70,8 +70,9 @@ my_data_test <- as.matrix(bank_test[, 1:16, with = FALSE])
# The categorical features can be passed to lgb.train to not copy and paste a lot # The categorical features can be passed to lgb.train to not copy and paste a lot
dtrain <- lgb.Dataset(data = my_data_train, dtrain <- lgb.Dataset(data = my_data_train,
label = bank_train$y) label = bank_train$y)
dtest <- lgb.Dataset(data = my_data_test, dtest <- lgb.Dataset.create.valid(dtrain,
label = bank_test$y) data = my_data_test,
label = bank_test$y)
# We can now train a model # We can now train a model
model <- lgb.train(list(objective = "binary", model <- lgb.train(list(objective = "binary",
......
...@@ -3,7 +3,7 @@ require(lightgbm) ...@@ -3,7 +3,7 @@ require(lightgbm)
data(agaricus.train, package = "lightgbm") data(agaricus.train, package = "lightgbm")
data(agaricus.test, package = "lightgbm") data(agaricus.test, package = "lightgbm")
dtrain <- lgb.Dataset(agaricus.train$data, label = agaricus.train$label) dtrain <- lgb.Dataset(agaricus.train$data, label = agaricus.train$label)
dtest <- lgb.Dataset(agaricus.test$data, label = agaricus.test$label) dtest <- lgb.Dataset.create.valid(dtrain, data = agaricus.test$data, label = agaricus.test$label)
nrounds <- 2 nrounds <- 2
param <- list(num_leaves = 4, param <- list(num_leaves = 4,
......
...@@ -6,7 +6,7 @@ data(agaricus.train, package = "lightgbm") ...@@ -6,7 +6,7 @@ data(agaricus.train, package = "lightgbm")
data(agaricus.test, package = "lightgbm") data(agaricus.test, package = "lightgbm")
dtrain <- lgb.Dataset(agaricus.train$data, label = agaricus.train$label) dtrain <- lgb.Dataset(agaricus.train$data, label = agaricus.train$label)
dtest <- lgb.Dataset(agaricus.test$data, label = agaricus.test$label) dtest <- lgb.Dataset.create.valid(dtrain, data = agaricus.test$data, label = agaricus.test$label)
# Note: for customized objective function, we leave objective as default # Note: for customized objective function, we leave objective as default
# Note: what we are getting is margin value in prediction # Note: what we are getting is margin value in prediction
......
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