[GitHub] srowen commented on a change in pull request #14325: [SPARK-16692] [ML] Add multi label classification evaluator, DataFrame

[GitBox <gi...@apache.org>]

srowen commented on a change in pull request #14325: [SPARK-16692] [ML] Add multi label classification evaluator, DataFrame
URL: https://github.com/apache/spark/pull/14325#discussion_r254299767
 
 

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 File path: mllib/src/main/scala/org/apache/spark/ml/evaluation/MultilabelClassificationEvaluator.scala
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+/*
+ * 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.{Experimental, Since}
+import org.apache.spark.ml.param.{Param, ParamMap, ParamValidators}
+import org.apache.spark.ml.param.shared.{HasLabelCol, HasPredictionCol}
+import org.apache.spark.ml.util.{DefaultParamsReadable, DefaultParamsWritable, Identifiable}
+import org.apache.spark.mllib.evaluation.MultilabelMetrics
+import org.apache.spark.sql.{DataFrame, Row}
+
+/**
+  * :: Experimental ::
+  * Evaluator for Multilabel classification, which expects two input columns: score and label.
+  */
+
+@Since("1.5.0")
+@Experimental
+class MultilabelClassificationEvaluator @Since("1.5.0") (@Since("1.5.0") override val uid: String)
+  extends HasPredictionCol with HasLabelCol with DefaultParamsWritable {
+  @Since("1.5.0")
+  def this() = this(Identifiable.randomUID("mlcEval"))
+
+  /**
+    * param for metric name in evaluation "f1Measure", "precision",
+      "recall", "accuracy", "microF1Measure", "microPrecision", "microRecall",
+      "hammingLoss", "fScoreByLabel", "precisionByLabel", "recallByLabel")
+    *
+    * @group param
+    */
+  @Since("1.5.0")
+  val metricName: Param[String] = {
+    val allowedParams = ParamValidators.inArray(Array("f1Measure", "precision",
+      "recall", "accuracy", "microF1Measure", "microPrecision", "microRecall",
+      "hammingLoss", "fScoreByLabel", "precisionByLabel", "recallByLabel"))
+    new Param(this, "metricName", "metric name in evaluation " +
+      "(f1Measure|precision|recall|accuracy|microF1Measure|microPrecision|microRecall" +
+      "|hammingLoss|fScoreByLabel|precisionByLabel|recallByLabel)", allowedParams)}
+
+  /** @group getParam */
+  @Since("1.5.0")
+  def getMetricName: String = $(metricName)
+
+  /** @group setParam */
+  @Since("1.5.0")
+  def setMetricName(value: String): this.type = set(metricName, value)
+
+  /** @group setParam */
+  @Since("1.5.0")
+  def setPredictionCol(value: String): this.type = set(predictionCol, value)
+
+  /** @group setParam */
+  @Since("1.5.0")
+  def setLabelCol(value: String): this.type = set(labelCol, value)
+
+  setDefault(metricName -> "f1Measure")
+
+  @Since("1.5.0")
+  def evaluate(dataset: DataFrame, label: Double = Double.NegativeInfinity): Double = {
+    val predictionAndLabels = dataset.select($(predictionCol), $(labelCol)).rdd.map {
+      case Row(prediction: Array[Double], labelData: Array[Double]) =>
+        (prediction, labelData)
+    }
+    val metrics = new MultilabelMetrics(predictionAndLabels)
+    var metric = 0.0
+    metric = $( metricName ) match {
 
 Review comment:
   Nit: no space around parens

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