Repository: spark Updated Branches: refs/heads/master 6327ea570 -> 6077e3ef3
[SPARK-21801][SPARKR][TEST] unit test randomly fail with randomforest ## What changes were proposed in this pull request? fix the random seed to eliminate variability ## How was this patch tested? jenkins, appveyor, lots more jenkins Author: Felix Cheung <felixcheun...@hotmail.com> Closes #19018 from felixcheung/rrftest. Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/6077e3ef Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/6077e3ef Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/6077e3ef Branch: refs/heads/master Commit: 6077e3ef3cb39fab061cbf6a357423da030c47c4 Parents: 6327ea5 Author: Felix Cheung <felixcheun...@hotmail.com> Authored: Tue Aug 29 10:09:41 2017 -0700 Committer: Felix Cheung <felixche...@apache.org> Committed: Tue Aug 29 10:09:41 2017 -0700 ---------------------------------------------------------------------- R/pkg/tests/fulltests/test_mllib_tree.R | 36 +++++++++++++++------------- 1 file changed, 19 insertions(+), 17 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/6077e3ef/R/pkg/tests/fulltests/test_mllib_tree.R ---------------------------------------------------------------------- diff --git a/R/pkg/tests/fulltests/test_mllib_tree.R b/R/pkg/tests/fulltests/test_mllib_tree.R index 799f944..facd3a9 100644 --- a/R/pkg/tests/fulltests/test_mllib_tree.R +++ b/R/pkg/tests/fulltests/test_mllib_tree.R @@ -66,7 +66,7 @@ test_that("spark.gbt", { # label must be binary - GBTClassifier currently only supports binary classification. iris2 <- iris[iris$Species != "virginica", ] data <- suppressWarnings(createDataFrame(iris2)) - model <- spark.gbt(data, Species ~ Petal_Length + Petal_Width, "classification") + model <- spark.gbt(data, Species ~ Petal_Length + Petal_Width, "classification", seed = 12) stats <- summary(model) expect_equal(stats$numFeatures, 2) expect_equal(stats$numTrees, 20) @@ -94,7 +94,7 @@ test_that("spark.gbt", { iris2$NumericSpecies <- ifelse(iris2$Species == "setosa", 0, 1) df <- suppressWarnings(createDataFrame(iris2)) - m <- spark.gbt(df, NumericSpecies ~ ., type = "classification") + m <- spark.gbt(df, NumericSpecies ~ ., type = "classification", seed = 12) s <- summary(m) # test numeric prediction values expect_equal(iris2$NumericSpecies, as.double(collect(predict(m, df))$prediction)) @@ -106,7 +106,7 @@ test_that("spark.gbt", { if (windows_with_hadoop()) { data <- read.df(absoluteSparkPath("data/mllib/sample_binary_classification_data.txt"), source = "libsvm") - model <- spark.gbt(data, label ~ features, "classification") + model <- spark.gbt(data, label ~ features, "classification", seed = 12) expect_equal(summary(model)$numFeatures, 692) } @@ -117,10 +117,11 @@ test_that("spark.gbt", { trainidxs <- base::sample(nrow(data), nrow(data) * 0.7) traindf <- as.DataFrame(data[trainidxs, ]) testdf <- as.DataFrame(rbind(data[-trainidxs, ], c(0, "the other"))) - model <- spark.gbt(traindf, clicked ~ ., type = "classification") + model <- spark.gbt(traindf, clicked ~ ., type = "classification", seed = 23) predictions <- predict(model, testdf) expect_error(collect(predictions)) - model <- spark.gbt(traindf, clicked ~ ., type = "classification", handleInvalid = "keep") + model <- spark.gbt(traindf, clicked ~ ., type = "classification", handleInvalid = "keep", + seed = 23) predictions <- predict(model, testdf) expect_equal(class(collect(predictions)$clicked[1]), "character") }) @@ -129,7 +130,7 @@ test_that("spark.randomForest", { # regression data <- suppressWarnings(createDataFrame(longley)) model <- spark.randomForest(data, Employed ~ ., "regression", maxDepth = 5, maxBins = 16, - numTrees = 1) + numTrees = 1, seed = 1) predictions <- collect(predict(model, data)) expect_equal(predictions$prediction, c(60.323, 61.122, 60.171, 61.187, @@ -177,7 +178,7 @@ test_that("spark.randomForest", { # classification data <- suppressWarnings(createDataFrame(iris)) model <- spark.randomForest(data, Species ~ Petal_Length + Petal_Width, "classification", - maxDepth = 5, maxBins = 16) + maxDepth = 5, maxBins = 16, seed = 123) stats <- summary(model) expect_equal(stats$numFeatures, 2) @@ -215,7 +216,7 @@ test_that("spark.randomForest", { iris$NumericSpecies <- lapply(iris$Species, labelToIndex) data <- suppressWarnings(createDataFrame(iris[-5])) model <- spark.randomForest(data, NumericSpecies ~ Petal_Length + Petal_Width, "classification", - maxDepth = 5, maxBins = 16) + maxDepth = 5, maxBins = 16, seed = 123) stats <- summary(model) expect_equal(stats$numFeatures, 2) expect_equal(stats$numTrees, 20) @@ -234,12 +235,12 @@ test_that("spark.randomForest", { traindf <- as.DataFrame(data[trainidxs, ]) testdf <- as.DataFrame(rbind(data[-trainidxs, ], c(0, "the other"))) model <- spark.randomForest(traindf, clicked ~ ., type = "classification", - maxDepth = 10, maxBins = 10, numTrees = 10) + maxDepth = 10, maxBins = 10, numTrees = 10, seed = 123) predictions <- predict(model, testdf) expect_error(collect(predictions)) model <- spark.randomForest(traindf, clicked ~ ., type = "classification", maxDepth = 10, maxBins = 10, numTrees = 10, - handleInvalid = "keep") + handleInvalid = "keep", seed = 123) predictions <- predict(model, testdf) expect_equal(class(collect(predictions)$clicked[1]), "character") @@ -247,7 +248,7 @@ test_that("spark.randomForest", { if (windows_with_hadoop()) { data <- read.df(absoluteSparkPath("data/mllib/sample_multiclass_classification_data.txt"), source = "libsvm") - model <- spark.randomForest(data, label ~ features, "classification") + model <- spark.randomForest(data, label ~ features, "classification", seed = 123) expect_equal(summary(model)$numFeatures, 4) } }) @@ -255,7 +256,8 @@ test_that("spark.randomForest", { test_that("spark.decisionTree", { # regression data <- suppressWarnings(createDataFrame(longley)) - model <- spark.decisionTree(data, Employed ~ ., "regression", maxDepth = 5, maxBins = 16) + model <- spark.decisionTree(data, Employed ~ ., "regression", maxDepth = 5, maxBins = 16, + seed = 42) predictions <- collect(predict(model, data)) expect_equal(predictions$prediction, c(60.323, 61.122, 60.171, 61.187, @@ -288,7 +290,7 @@ test_that("spark.decisionTree", { # classification data <- suppressWarnings(createDataFrame(iris)) model <- spark.decisionTree(data, Species ~ Petal_Length + Petal_Width, "classification", - maxDepth = 5, maxBins = 16) + maxDepth = 5, maxBins = 16, seed = 43) stats <- summary(model) expect_equal(stats$numFeatures, 2) @@ -325,7 +327,7 @@ test_that("spark.decisionTree", { iris$NumericSpecies <- lapply(iris$Species, labelToIndex) data <- suppressWarnings(createDataFrame(iris[-5])) model <- spark.decisionTree(data, NumericSpecies ~ Petal_Length + Petal_Width, "classification", - maxDepth = 5, maxBins = 16) + maxDepth = 5, maxBins = 16, seed = 44) stats <- summary(model) expect_equal(stats$numFeatures, 2) expect_equal(stats$maxDepth, 5) @@ -339,7 +341,7 @@ test_that("spark.decisionTree", { if (windows_with_hadoop()) { data <- read.df(absoluteSparkPath("data/mllib/sample_multiclass_classification_data.txt"), source = "libsvm") - model <- spark.decisionTree(data, label ~ features, "classification") + model <- spark.decisionTree(data, label ~ features, "classification", seed = 45) expect_equal(summary(model)$numFeatures, 4) } @@ -351,11 +353,11 @@ test_that("spark.decisionTree", { traindf <- as.DataFrame(data[trainidxs, ]) testdf <- as.DataFrame(rbind(data[-trainidxs, ], c(0, "the other"))) model <- spark.decisionTree(traindf, clicked ~ ., type = "classification", - maxDepth = 5, maxBins = 16) + maxDepth = 5, maxBins = 16, seed = 46) predictions <- predict(model, testdf) expect_error(collect(predictions)) model <- spark.decisionTree(traindf, clicked ~ ., type = "classification", - maxDepth = 5, maxBins = 16, handleInvalid = "keep") + maxDepth = 5, maxBins = 16, handleInvalid = "keep", seed = 46) predictions <- predict(model, testdf) expect_equal(class(collect(predictions)$clicked[1]), "character") }) --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org
