Nothing
require(xgboost)
context("interaction constraints")
n_threads <- 2
set.seed(1024)
x1 <- rnorm(1000, 1)
x2 <- rnorm(1000, 1)
x3 <- sample(c(1, 2, 3), size = 1000, replace = TRUE)
y <- x1 + x2 + x3 + x1 * x2 * x3 + rnorm(1000, 0.001) + 3 * sin(x1)
train <- matrix(c(x1, x2, x3), ncol = 3)
test_that("interaction constraints scientific representation", {
rows <- 10
## When number exceeds 1e5, R paste function uses scientific representation.
## See: https://github.com/dmlc/xgboost/issues/5179
cols <- 1e5 + 10
d <- matrix(rexp(rows, rate = .1), nrow = rows, ncol = cols)
y <- rnorm(rows)
dtrain <- xgb.DMatrix(data = d, info = list(label = y), nthread = n_threads)
inc <- list(c(seq.int(from = 0, to = cols, by = 1)))
with_inc <- xgb.train(
data = dtrain,
tree_method = 'hist',
interaction_constraints = inc,
nrounds = 10,
nthread = n_threads
)
without_inc <- xgb.train(
data = dtrain, tree_method = 'hist', nrounds = 10, nthread = n_threads
)
expect_equal(xgb.save.raw(with_inc), xgb.save.raw(without_inc))
})
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