41 lines
1.3 KiB
R
41 lines
1.3 KiB
R
context('Test helper functions')
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require(xgboost)
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require(data.table)
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require(Matrix)
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require(vcd)
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set.seed(1994)
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data(Arthritis)
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data(agaricus.train, package='xgboost')
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df <- data.table(Arthritis, keep.rownames = F)
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df[,AgeDiscret := as.factor(round(Age / 10,0))]
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df[,AgeCat := as.factor(ifelse(Age > 30, "Old", "Young"))]
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df[,ID := NULL]
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sparse_matrix <- sparse.model.matrix(Improved~.-1, data = df)
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output_vector <- df[,Y := 0][Improved == "Marked",Y := 1][,Y]
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bst <- xgboost(data = sparse_matrix, label = output_vector, max.depth = 9,
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eta = 1, nthread = 2, nround = 10,objective = "binary:logistic")
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test_that("xgb.dump works", {
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capture.output(print(xgb.dump(bst)))
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expect_true(xgb.dump(bst, 'xgb.model.dump', with.stats = T))
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})
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test_that("xgb.importance works", {
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importance <- xgb.importance(sparse_matrix@Dimnames[[2]], model = bst)
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expect_equal(dim(importance), c(7, 4))
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expect_equal(colnames(importance), c("Feature", "Gain", "Cover", "Frequency"))
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})
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test_that("xgb.plot.tree works", {
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xgb.plot.tree(names = agaricus.train$data@Dimnames[[2]], model = bst)
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})
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test_that("xgb.plot.deepness works", {
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xgb.plot.deepness(model = bst)
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})
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test_that("xgb.plot.multi.trees works", {
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xgb.plot.multi.trees(model = bst, names = agaricus.train$data@Dimnames[[2]], 3)
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}) |