zero323 commented on a change in pull request #27570: [SPARK-30820][SPARKR][ML]
Add FMClassifier to SparkR
URL: https://github.com/apache/spark/pull/27570#discussion_r379893973
##########
File path: R/pkg/tests/fulltests/test_mllib_classification.R
##########
@@ -488,4 +488,36 @@ test_that("spark.naiveBayes", {
expect_equal(class(collect(predictions)$clicked[1]), "character")
})
+test_that("spark.fmClassifier", {
+ df <- withColumn(
+ suppressWarnings(createDataFrame(iris)),
+ "Species", otherwise(when(column("Species") == "Setosa", "Setosa"),
"Not-Setosa")
+ )
+
+ model1 <- spark.fmClassifier(
+ df, Species ~ .,
+ regParam = 0.01, maxIter = 10, fitLinear = TRUE, factorSize = 3
+ )
+
+ prediction1 <- predict(model1, df)
+ expect_is(prediction1, "SparkDataFrame")
Review comment:
I am not sure if such check are really useful here. In practice fitting is
not unlikely failure point and most likely problems are related to parameter
passing.
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