Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/6344#discussion_r30871422
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/evaluation/RegressionEvaluator.scala
---
@@ -0,0 +1,85 @@
+/*
+ * 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.evaluation
+
+import org.apache.spark.annotation.AlphaComponent
+import org.apache.spark.ml.Evaluator
+import org.apache.spark.ml.param.Param
+import org.apache.spark.ml.param.shared.{HasLabelCol, HasPredictionCol}
+import org.apache.spark.ml.util.{Identifiable, SchemaUtils}
+import org.apache.spark.mllib.evaluation.RegressionMetrics
+import org.apache.spark.sql.{DataFrame, Row}
+import org.apache.spark.sql.types.DoubleType
+
+/**
+ * :: AlphaComponent ::
+ *
+ * Evaluator for regression, which expects two input columns: score and
label.
+ */
+@AlphaComponent
+class RegressionEvaluator(override val uid: String)
+ extends Evaluator with HasPredictionCol with HasLabelCol {
+
+ def this() = this(Identifiable.randomUID("regEval"))
+
+ /**
+ * param for metric name in evaluation
+ * @group param
+ */
+ val metricName: Param[String] = new Param(this, "metricName",
+ "metric name in evaluation (rmse|r2|mae)")
+
+ /** @group getParam */
+ def getMetricName: String = $(metricName)
+
+ /** @group setParam */
+ def setMetricName(value: String): this.type = set(metricName, value)
+
+ /** @group setParam */
+ def setScoreCol(value: String): this.type = set(predictionCol, value)
+
+ /** @group setParam */
+ def setLabelCol(value: String): this.type = set(labelCol, value)
+
+ setDefault(metricName -> "rmse")
+
+ override def evaluate(dataset: DataFrame): Double = {
+ val schema = dataset.schema
+ SchemaUtils.checkColumnType(schema, $(predictionCol), DoubleType)
+ SchemaUtils.checkColumnType(schema, $(labelCol), DoubleType)
+
+ val scoreAndLabels = dataset.select($(predictionCol), $(labelCol))
+ .map { case Row(prediction: Double, label: Double) =>
+ (prediction, label)
+ }
+ val metrics = new RegressionMetrics(scoreAndLabels)
+ val metric = $(metricName) match {
+ case "rmse" =>
+ metrics.rootMeanSquaredError
+ case "mse" =>
+ metrics.meanSquaredError
+ case "r2" =>
+ metrics.r2
+ case "mae" =>
+ metrics.meanAbsoluteError
+ case other =>
--- End diff --
This check should happen in the validator of param `metricName`. See:
https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/param/params.scala#L165
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