Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/20257#discussion_r161477464
--- Diff:
examples/src/main/scala/org/apache/spark/examples/ml/OneHotEncoderEstimatorExample.scala
---
@@ -0,0 +1,67 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+// scalastyle:off println
+package org.apache.spark.examples.ml
+
+// $example on$
+import org.apache.spark.ml.feature.{OneHotEncoderEstimator, StringIndexer}
+// $example off$
+import org.apache.spark.sql.SparkSession
+
+object OneHotEncoderEstimatorExample {
+ def main(args: Array[String]): Unit = {
+ val spark = SparkSession
+ .builder
+ .appName("OneHotEncoderEstimatorExample")
+ .getOrCreate()
+
+ // $example on$
+ val df = spark.createDataFrame(Seq(
--- End diff --
I know the examples are re-creating the existing `OneHotEncoder` examples,
but perhaps we should just drop the `StringIndexer` part and show a simplified
example transforming the raw label indices to OHE vectors?
We could mention in the user guide that it is common to encode categorical
features using `StringIndexer` first?
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