Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/15851#discussion_r87643716
--- Diff: R/pkg/inst/tests/testthat/test_mllib.R ---
@@ -971,10 +971,15 @@ test_that("spark.randomForest Classification", {
predictions <- collect(predict(model, data))$prediction
expect_equal(length(grep("1.0", predictions)), 50)
expect_equal(length(grep("2.0", predictions)), 50)
+
+ # spark.randomForest classification can work on libsvm data
+ data <-
read.df(absoluteSparkPath("data/mllib/sample_multiclass_classification_data.txt"),
+ source = "libsvm")
+ model <- spark.randomForest(data, label ~ features, "classification")
+ expect_equal(summary(model)$numFeatures, 4)
--- End diff --
one minor nit is though the tests for glm or naiveBayes are earlier on so
we might want to test this there instead of a later test like randomForest or
gbt.
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