Minor addition to R unit tests
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@ -6,14 +6,15 @@ data(agaricus.train, package='xgboost')
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data(agaricus.test, package='xgboost')
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train <- agaricus.train
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test <- agaricus.test
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set.seed(1994)
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test_that("train and predict", {
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bst <- xgboost(data = train$data, label = train$label, max.depth = 2,
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eta = 1, nthread = 2, nround = 2, objective = "binary:logistic")
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pred <- predict(bst, test$data)
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expect_equal(length(pred), 1611)
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})
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test_that("early stopping", {
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res <- xgb.cv(data = train$data, label = train$label, max.depth = 2, nfold = 5,
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eta = 0.3, nthread = 2, nround = 20, objective = "binary:logistic",
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@ -23,6 +24,7 @@ test_that("early stopping", {
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eta = 0.3, nthread = 2, nround = 20, objective = "binary:logistic",
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early.stop.round = 3, maximize = FALSE)
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pred <- predict(bst, test$data)
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expect_equal(length(pred), 1611)
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})
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test_that("save_period", {
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@ -30,4 +32,5 @@ test_that("save_period", {
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eta = 0.3, nthread = 2, nround = 20, objective = "binary:logistic",
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save_period = 10, save_name = "xgb.model")
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pred <- predict(bst, test$data)
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expect_equal(length(pred), 1611)
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})
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@ -5,6 +5,7 @@ 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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@ -16,15 +17,16 @@ 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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dump <- xgb.dump(bst)
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expect_equal(length(dump, 172))
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})
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test_that("xgb.importance works", {
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xgb.dump(bst, 'xgb.model.dump', with.stats = T)
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expect_true(xgb.dump(bst, 'xgb.model.dump', with.stats = T))
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importance <- xgb.importance(sparse_matrix@Dimnames[[2]], 'xgb.model.dump')
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expect_equal(dim(importance), c(7, 4))
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expect_equal(colnames(importance), c("Feature", "Gain", "Cover", "Frequence"))
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})
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test_that("xgb.plot.tree works", {
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@ -1,6 +1,7 @@
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context('Test poisson regression model')
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require(xgboost)
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set.seed(1994)
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test_that("poisson regression works", {
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data(mtcars)
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@ -9,5 +10,5 @@ test_that("poisson regression works", {
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expect_equal(class(bst), "xgb.Booster")
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pred <- predict(bst,as.matrix(mtcars[, -11]))
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expect_equal(length(pred), 32)
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sqrt(mean( (pred - mtcars[,11]) ^ 2))
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})
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expect_equal(sqrt(mean( (pred - mtcars[,11]) ^ 2)), 1.16, tolerance = 0.01)
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})
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