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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2019/05/27 13:59:19 UTC

[GitHub] [spark] srowen commented on a change in pull request #24717: [SPARK-27847][ML] One-Pass MultilabelMetrics & MulticlassMetrics

srowen commented on a change in pull request #24717: [SPARK-27847][ML] One-Pass MultilabelMetrics & MulticlassMetrics
URL: https://github.com/apache/spark/pull/24717#discussion_r287792148
 
 

 ##########
 File path: mllib/src/main/scala/org/apache/spark/mllib/evaluation/MultilabelMetrics.scala
 ##########
 @@ -179,3 +167,160 @@ class MultilabelMetrics @Since("1.2.0") (predictionAndLabels: RDD[(Array[Double]
   @Since("1.2.0")
   lazy val labels: Array[Double] = tpPerClass.keys.toArray.sorted
 }
+
+
+/**
+ * Trait for statistical summary for multi-label metrics.
+ */
+private[evaluation] trait MultilabelSummary {
+
+  def numDocs: Long
+
+  def numLabels: Long
+
+  def subsetAccuracy: Double
+
+  def accuracy: Double
+
+  def hammingLoss: Double
+
+  def precision: Double
+
+  def recall: Double
+
+  def f1Measure: Double
+
+  def tpPerClass: Map[Double, Long]
+
+  def fpPerClass: Map[Double, Long]
+
+  def fnPerClass: Map[Double, Long]
+}
+
+
+private[evaluation] class MultilabelSummarizer extends MultilabelSummary with Serializable {
+
+  private var docCnt = 0L
+  private val labelSet = mutable.Set.empty[Double]
+  private var subsetAccuracyCnt = 0L
+  private var accuracySum = 0.0
+  private var hammingLossSum = 0L
+  private var precisionSum = 0.0
+  private var recallSum = 0.0
+  private var f1MeasureSum = 0.0
+  private val tpPerClass_ = mutable.Map.empty[Double, Long]
+  private val fpPerClass_ = mutable.Map.empty[Double, Long]
+  private val fnPerClass_ = mutable.Map.empty[Double, Long]
+
+  /**
+   * Add a new sample (predictions and labels) to this summarizer, and update
+   * the statistical summary.
+   *
+   * @return This MultilabelSummarizer object.
+   */
+  def add(predictions: Array[Double], labels: Array[Double]): this.type = {
+    val intersection = predictions.intersect(labels)
+
+    docCnt += 1L
+
+    labels.foreach(labelSet.add)
 
 Review comment:
   `labelSet ++= labels`?

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