huaxingao 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_r386510001
##########
File path: R/pkg/tests/fulltests/test_mllib_classification.R
##########
@@ -488,4 +488,36 @@ test_that("spark.naiveBayes", {
expect_equal(class(collect(predictions)$clicked[1]), "character")
})
+test_that("spark.fmClassifier", {
+ df <- withColumn(
+ suppressWarnings(createDataFrame(iris)),
+ "Species", otherwise(when(column("Species") == "Setosa", "Setosa"),
"Not-Setosa")
+ )
+
+ model1 <- spark.fmClassifier(
+ df, Species ~ .,
+ regParam = 0.01, maxIter = 10, fitLinear = TRUE, factorSize = 3
+ )
+
+ prediction1 <- predict(model1, df)
+ expect_is(prediction1, "SparkDataFrame")
Review comment:
Seems to me that all the other ML R tests check the prediction result. For
example, in LinearSVM,
```
# Test prediction with string label
prediction <- predict(model, training)
expect_equal(typeof(take(select(prediction, "prediction"), 1)$prediction),
"character")
expected <- c("versicolor", "versicolor", "versicolor", "virginica",
"virginica",
"virginica", "virginica", "virginica", "virginica",
"virginica")
expect_equal(sort(as.list(take(select(prediction, "prediction"),
10))[[1]]), expected)
```
Is it OK if we do something similar here?
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