Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/304#discussion_r11462172
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/preprocessing/OneHotEncoder.scala
---
@@ -0,0 +1,112 @@
+/*
+ * 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.mllib.preprocessing
+
+import org.apache.spark.rdd.RDD
+
+import scala.collection.mutable.HashSet
+import scala.collection.mutable.Set
+
+/**
+ * A utility for encoding categorical variables as numeric variables. The
resulting vectors
+ * contain a component for each value that the variable can take. The
component corresponding
+ * to the value that the variable takes is set to 1 and the components
corresponding to all other
+ * categories are set to 0.
+ *
+ * The utility handles input vectors with mixed categorical and numeric
variables by accepting a
+ * list of feature indices that are categorical and only transforming
those.
+ *
+ * An example usage is:
+ *
+ * {{{
+ * val categoricalFields = Array(0, 7, 21)
+ * val categories = OneHotEncoder.categories(rdd, categoricalFields)
+ * val encoded = OneHotEncoder.encode(rdd, categories)
+ * }}}
+ */
+object OneHotEncoder {
+
+ /**
+ * Given a dataset and the set of columns which are categorical
variables, returns a structure
+ * that, for each field, describes the values that are present for in
the dataset. The structure
+ * is meant to be used as input to encode.
+ */
+ def categories(rdd: RDD[Array[Any]], categoricalFields: Seq[Int]):
Array[Map[Any, Int]] = {
+ val categories = rdd.map(categoricals(_,
categoricalFields)).reduce(uniqueCats)
+
+ val catMaps = new Array[Map[Any, Int]](rdd.first().length)
--- End diff --
`catMaps` should have the same size as `categoricalFields` to save space.
The worst case is when the dimension is huge but number of categorical features
is small.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
