[SPARK-50963][ML][PYTHON][TESTS][FOLLOW-UP] Enable a parity test

### What changes were proposed in this pull request?
Enable a existing test on connect, move it after `test_stop_words_remover` and rename it

### Why are the changes needed?
for test coverage

### Does this PR introduce _any_ user-facing change?
no, test-only

### How was this patch tested?
parity test

### Was this patch authored or co-authored using generative AI tooling?
no

Closes #49642 from zhengruifeng/ml_remover_test.

Authored-by: Ruifeng Zheng <ruifengz@apache.org>
Signed-off-by: Ruifeng Zheng <ruifengz@apache.org>

Author: zhengruifeng

python/pyspark/ml/tests/connect/test_parity_feature.py

@@ -34,10 +34,6 @@ def test_idf(self):
     def test_ngram(self):
         super().test_ngram()
 
-    @unittest.skip("Need to support.")
-    def test_stopwordsremover(self):
-        super().test_stopwordsremover()
-
     @unittest.skip("Need to support.")
     def test_count_vectorizer_with_binary(self):
         super().test_count_vectorizer_with_binary()

python/pyspark/ml/tests/test_feature.py

@@ -517,6 +517,37 @@ def test_stop_words_remover(self):
             remover2 = StopWordsRemover.load(d)
             self.assertEqual(str(remover), str(remover2))
 
+    def test_stop_words_remover_II(self):
+        dataset = self.spark.createDataFrame([Row(input=["a", "panda"])])
+        stopWordRemover = StopWordsRemover(inputCol="input", outputCol="output")
+        # Default
+        self.assertEqual(stopWordRemover.getInputCol(), "input")
+        transformedDF = stopWordRemover.transform(dataset)
+        self.assertEqual(transformedDF.head().output, ["panda"])
+        self.assertEqual(type(stopWordRemover.getStopWords()), list)
+        self.assertTrue(isinstance(stopWordRemover.getStopWords()[0], str))
+        # Custom
+        stopwords = ["panda"]
+        stopWordRemover.setStopWords(stopwords)
+        self.assertEqual(stopWordRemover.getInputCol(), "input")
+        self.assertEqual(stopWordRemover.getStopWords(), stopwords)
+        transformedDF = stopWordRemover.transform(dataset)
+        self.assertEqual(transformedDF.head().output, ["a"])
+        # with language selection
+        stopwords = StopWordsRemover.loadDefaultStopWords("turkish")
+        dataset = self.spark.createDataFrame([Row(input=["acaba", "ama", "biri"])])
+        stopWordRemover.setStopWords(stopwords)
+        self.assertEqual(stopWordRemover.getStopWords(), stopwords)
+        transformedDF = stopWordRemover.transform(dataset)
+        self.assertEqual(transformedDF.head().output, [])
+        # with locale
+        stopwords = ["BELKİ"]
+        dataset = self.spark.createDataFrame([Row(input=["belki"])])
+        stopWordRemover.setStopWords(stopwords).setLocale("tr")
+        self.assertEqual(stopWordRemover.getStopWords(), stopwords)
+        transformedDF = stopWordRemover.transform(dataset)
+        self.assertEqual(transformedDF.head().output, [])
+
     def test_binarizer(self):
         b0 = Binarizer()
         self.assertListEqual(
@@ -570,37 +601,6 @@ def test_ngram(self):
         transformedDF = ngram0.transform(dataset)
         self.assertEqual(transformedDF.head().output, ["a b c d", "b c d e"])
 
-    def test_stopwordsremover(self):
-        dataset = self.spark.createDataFrame([Row(input=["a", "panda"])])
-        stopWordRemover = StopWordsRemover(inputCol="input", outputCol="output")
-        # Default
-        self.assertEqual(stopWordRemover.getInputCol(), "input")
-        transformedDF = stopWordRemover.transform(dataset)
-        self.assertEqual(transformedDF.head().output, ["panda"])
-        self.assertEqual(type(stopWordRemover.getStopWords()), list)
-        self.assertTrue(isinstance(stopWordRemover.getStopWords()[0], str))
-        # Custom
-        stopwords = ["panda"]
-        stopWordRemover.setStopWords(stopwords)
-        self.assertEqual(stopWordRemover.getInputCol(), "input")
-        self.assertEqual(stopWordRemover.getStopWords(), stopwords)
-        transformedDF = stopWordRemover.transform(dataset)
-        self.assertEqual(transformedDF.head().output, ["a"])
-        # with language selection
-        stopwords = StopWordsRemover.loadDefaultStopWords("turkish")
-        dataset = self.spark.createDataFrame([Row(input=["acaba", "ama", "biri"])])
-        stopWordRemover.setStopWords(stopwords)
-        self.assertEqual(stopWordRemover.getStopWords(), stopwords)
-        transformedDF = stopWordRemover.transform(dataset)
-        self.assertEqual(transformedDF.head().output, [])
-        # with locale
-        stopwords = ["BELKİ"]
-        dataset = self.spark.createDataFrame([Row(input=["belki"])])
-        stopWordRemover.setStopWords(stopwords).setLocale("tr")
-        self.assertEqual(stopWordRemover.getStopWords(), stopwords)
-        transformedDF = stopWordRemover.transform(dataset)
-        self.assertEqual(transformedDF.head().output, [])
-
     def test_count_vectorizer_with_binary(self):
         dataset = self.spark.createDataFrame(
             [