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| author | Xusen Yin <yinxusen@gmail.com> | 2016-02-23 15:42:58 -0800 |
|---|---|---|
| committer | Xiangrui Meng <meng@databricks.com> | 2016-02-23 15:42:58 -0800 |
| commit | 8d29001dec5c3695721a76df3f70da50512ef28f (patch) | |
| tree | dcb610ddff00188cf9898cce6d3eee029c44010b /R/pkg/inst/tests | |
| parent | 15e30155631d52e35ab8522584027ab350e5acb3 (diff) | |
| download | spark-8d29001dec5c3695721a76df3f70da50512ef28f.tar.gz spark-8d29001dec5c3695721a76df3f70da50512ef28f.tar.bz2 spark-8d29001dec5c3695721a76df3f70da50512ef28f.zip | |
[SPARK-13011] K-means wrapper in SparkR
https://issues.apache.org/jira/browse/SPARK-13011
Author: Xusen Yin <yinxusen@gmail.com>
Closes #11124 from yinxusen/SPARK-13011.
Diffstat (limited to 'R/pkg/inst/tests')
| -rw-r--r-- | R/pkg/inst/tests/testthat/test_mllib.R | 28 |
1 files changed, 28 insertions, 0 deletions
diff --git a/R/pkg/inst/tests/testthat/test_mllib.R b/R/pkg/inst/tests/testthat/test_mllib.R index 08099dd96a..595512e0e0 100644 --- a/R/pkg/inst/tests/testthat/test_mllib.R +++ b/R/pkg/inst/tests/testthat/test_mllib.R @@ -113,3 +113,31 @@ test_that("summary works on base GLM models", { baseSummary <- summary(baseModel) expect_true(abs(baseSummary$deviance - 12.19313) < 1e-4) }) + +test_that("kmeans", { + newIris <- iris + newIris$Species <- NULL + training <- suppressWarnings(createDataFrame(sqlContext, newIris)) + + # Cache the DataFrame here to work around the bug SPARK-13178. + cache(training) + take(training, 1) + + model <- kmeans(x = training, centers = 2) + sample <- take(select(predict(model, training), "prediction"), 1) + expect_equal(typeof(sample$prediction), "integer") + expect_equal(sample$prediction, 1) + + # Test stats::kmeans is working + statsModel <- kmeans(x = newIris, centers = 2) + expect_equal(unique(statsModel$cluster), c(1, 2)) + + # Test fitted works on KMeans + fitted.model <- fitted(model) + expect_equal(sort(collect(distinct(select(fitted.model, "prediction")))$prediction), c(0, 1)) + + # Test summary works on KMeans + summary.model <- summary(model) + cluster <- summary.model$cluster + expect_equal(sort(collect(distinct(select(cluster, "prediction")))$prediction), c(0, 1)) +}) |