Github user manishamde commented on a diff in the pull request:
https://github.com/apache/spark/pull/1582#discussion_r15497700
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/DTRegressorParams.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.
+ */
+
+package org.apache.spark.mllib.tree.configuration
+
+import org.apache.spark.annotation.Experimental
+import org.apache.spark.mllib.tree.impurity.RegressionImpurities
+
+/**
+ * :: Experimental ::
+ * Stores all the configuration options for DecisionTreeRegressor
construction
+ * @param impurity Criterion used for information gain calculation.
+ * Currently supported: "variance"
+ * @param maxDepth Maximum depth of the tree.
+ * E.g., depth 0 means 1 leaf node; depth 1 means 1
internal node + 2 leaf nodes.
+ * @param maxBins maximum number of bins used for splitting features
+ * @param quantileStrategy algorithm for calculating quantiles
+ * @param maxMemoryInMB maximum memory in MB allocated to histogram
aggregation. Default value is
+ * 128 MB.
+ */
+@Experimental
+class DTRegressorParams (
+ var impurity: String = "variance",
+ maxDepth: Int = 4,
+ maxBins: Int = 100,
+ quantileStrategy: String = "sort",
+ maxMemoryInMB: Int = 128)
+ extends DTParams(maxDepth, maxBins, quantileStrategy, maxMemoryInMB) {
+
+ def getImpurity: String = this.impurity
+
+ def setImpurity(impurity: String) = {
+ if (!RegressionImpurities.nameToImpurityMap.contains(impurity)) {
+ throw new IllegalArgumentException(s"Bad impurity parameter for
regression: $impurity")
--- End diff --
Mentioning supported impurities might help since such errors are generally
typos.
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