Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/23231#discussion_r239011539
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/feature/OneHotEncoderEstimator.scala
---
@@ -0,0 +1,91 @@
+/*
+ * 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.
+ */
+
+package org.apache.spark.ml.feature
+
+import org.apache.spark.annotation.Since
+import org.apache.spark.ml.Estimator
+import org.apache.spark.ml.param._
+import org.apache.spark.ml.util._
+import org.apache.spark.sql.Dataset
+import org.apache.spark.sql.types.StructType
+
+/**
+ * A one-hot encoder that maps a column of category indices to a column of
binary vectors, with
+ * at most a single one-value per row that indicates the input category
index.
+ * For example with 5 categories, an input value of 2.0 would map to an
output vector of
+ * `[0.0, 0.0, 1.0, 0.0]`.
+ * The last category is not included by default (configurable via
`dropLast`),
+ * because it makes the vector entries sum up to one, and hence linearly
dependent.
+ * So an input value of 4.0 maps to `[0.0, 0.0, 0.0, 0.0]`.
+ *
+ * @note This is different from scikit-learn's OneHotEncoder, which keeps
all categories.
+ * The output vectors are sparse.
+ *
+ * When `handleInvalid` is configured to 'keep', an extra "category"
indicating invalid values is
+ * added as last category. So when `dropLast` is true, invalid values are
encoded as all-zeros
+ * vector.
+ *
+ * @note When encoding multi-column by using `inputCols` and `outputCols`
params, input/output cols
+ * come in pairs, specified by the order in the arrays, and each pair is
treated independently.
+ *
+ * @note `OneHotEncoderEstimator` is renamed to `OneHotEncoder` in 3.0.0.
This
+ * `OneHotEncoderEstimator` is kept as an alias and will be removed in
further version.
+ *
+ * @see `StringIndexer` for converting categorical values into category
indices
+ */
+@Since("2.3.0")
--- End diff --
These since tags are from original OneHotEncoderEstimator.
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