[GitHub] [spark] zero323 commented on a change in pull request #27570: [SPARK-30820][SPARKR][ML] Add FMClassifier to SparkR

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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_r403581036
 
 

 ##########
 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")
+  expect_equal(summary(model1)$factorSize, 3)
+
+  # Test model save/load
+  if (windows_with_hadoop()) {
+    modelPath <- tempfile(pattern = "spark-fmclassifier", fileext = ".tmp")
+    write.ml(model1, modelPath)
+    model2 <- read.ml(modelPath)
+
+    expect_is(model2, "FMClassificationModel")
+
+    prediction2 <- predict(model2, df)
+    expect_equal(
+      collect(drop(prediction1, c("rawPrediction", "probability"))),
+      collect(drop(prediction2, c("rawPrediction", "probability")))
+    )
 
 Review comment:
   > Also, I prefer to follow what the other tests do for testing model save and load: checking if the loaded model has the same fields as the saved model. 
   
   W test if summaries are equal
   
   ```
       expect_equal(summary(model1), summary(model2))
   ```
   
   so that should cover things.

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