Github user manishamde commented on a diff in the pull request:
https://github.com/apache/spark/pull/3000#discussion_r19633564
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/feature/DatasetIndexer.scala ---
@@ -0,0 +1,280 @@
+/*
+ * 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.feature
+
+import org.apache.spark.Logging
+import org.apache.spark.annotation.Experimental
+import org.apache.spark.mllib.linalg.{Vectors, DenseVector, SparseVector,
Vector}
+import org.apache.spark.rdd.RDD
+import org.apache.spark.util.collection.OpenHashSet
+
+/**
+ * :: Experimental ::
+ * Class for indexing columns in a dataset.
+ *
+ * This helps process a dataset of unknown vectors into a dataset with
some continuous features
+ * and some categorical features. The choice between continuous and
categorical is based upon
+ * a maxCategories parameter.
--- End diff --
maxCategories as a threshold is a good default. In the future, we may want
to add different criteria for some features. Thoughts? Moreover, should we have
a reasonable default value?
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