Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/216#discussion_r10941192
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/discretization/DiscretizerModel.scala
---
@@ -0,0 +1,50 @@
+/*
+ * 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.discretization
+
+import org.apache.spark.rdd.RDD
+
+/**
+ * DiscretizerModel provides a template with the basic methods for future
discretizers.
+ */
+trait DiscretizerModel extends Serializable {
+ /**
+ * Return the thresholds used to discretized the given feature
+ *
+ * @param feature The number of the feature to discretize
+ */
+ def getThresholdsForFeature(feature: Int): Seq[Double]
+
+ /**
+ * Return the thresholds used to discretized the given features
+ *
+ * @param features The number of the feature to discretize
+ */
+ def getThresholdsForFeature(features: Seq[Int]): Map[Int, Seq[Double]]
+
+ /**
+ * Return the thresholds used to discretized the continuous features
+ */
+ def getThresholdsForContinuousFeatures: Map[Int, Seq[Double]]
+
+ /**
+ * Discretizes an RDD
+ */
+ def discretize: RDD[_]
--- End diff --
This method is not clear to me. It takes no argument and returns an RDD of
undefined type. A `DiscretizerModel` may be trained on one RDD but applied to
another RDD.
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