Fix for model saving and loading

README.md

@@ -92,6 +92,15 @@ val pipeline = new Pipeline().setStages(Array(indexer, assembler, iForest))
 val model = pipeline.fit(dataset)
 val predictions = model.transform(dataset)
 
+// Save pipeline model
+model.write.overwrite().save("/tmp/iforest.model")
+
+// Load pipeline model
+val loadedPipelineModel = PipelineModel.load("/tmp/iforest.model")
+// Get loaded iforest model
+val loadedIforestModel = loadedPipelineModel.stages(2).asInstanceOf[IForestModel]
+println(s"The loaded iforest model has no summary: model.hasSummary = ${loadedIforestModel.hasSummary}")
+
 val binaryMetrics = new BinaryClassificationMetrics(
 predictions.select("prediction", "label").rdd.map {
 case Row(label: Double, ground: Double) => (label, ground)
@@ -105,6 +114,10 @@ println(s"The model's auc: ${binaryMetrics.areaUnderROC()}")
 
 *Python API*
 ```python
+from pyspark.ml.linalg import Vectors
+import tempfile
+
+
 spark = SparkSession \
         .builder.master("local[*]") \
         .appName("IForestExample") \

src/main/scala/org/apache/spark/examples/ml/IForestExample.scala

 package org.apache.spark.examples.ml
 
-import org.apache.spark.ml.Pipeline
+import org.apache.spark.ml.{Pipeline, PipelineModel}
 import org.apache.spark.ml.feature.{StringIndexer, VectorAssembler}
-import org.apache.spark.ml.iforest.IForest
+import org.apache.spark.ml.iforest.{IForest, IForestModel}
 import org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
 import org.apache.spark.sql.{Row, SparkSession}
 
@@ -48,6 +48,15 @@ object IForestExample {
     val model = pipeline.fit(dataset)
     val predictions = model.transform(dataset)
 
+    // Save pipeline model
+    model.write.overwrite().save("/tmp/iforest.model")
+
+    // Load pipeline model
+    val loadedPipelineModel = PipelineModel.load("/tmp/iforest.model")
+    // Get loaded iforest model
+    val loadedIforestModel = loadedPipelineModel.stages(2).asInstanceOf[IForestModel]
+    println(s"The loaded iforest model has no summary: model.hasSummary = ${loadedIforestModel.hasSummary}")
+
     val binaryMetrics = new BinaryClassificationMetrics(
       predictions.select("prediction", "label").rdd.map {
         case Row(label: Double, ground: Double) => (label, ground)

src/main/scala/org/apache/spark/ml/iforest/IForest.scala

@@ -752,8 +752,8 @@ trait IForestParams extends Params {
     * Relative Error for Approximate Quantile (0 <= value <= 1),  default is 0.
     * @group param
     */
-  final val approxQuantileRelativeError: Param[Double] =
-    new Param[Double](parent = this, name ="approxQuantileRelativeError", doc = "relative error for approximate quantile")
+  final val approxQuantileRelativeError: DoubleParam =
+    new DoubleParam(parent = this, name ="approxQuantileRelativeError", doc = "relative error for approximate quantile")
 
   /** @group setParam */
   setDefault(approxQuantileRelativeError, value = 0d)

src/test/scala/org/apache/spark/ml/iforest/IForestSuite.scala

@@ -159,45 +159,45 @@ class IForestSuite extends SparkFunSuite with MLlibTestSparkContext with Default
     assert(model1.summary.anomalyScoreCol === model2.summary.anomalyScoreCol)
   }
 
-//  Uncomment the codes below to run the test for model read/write
-//  test("read/write") {
-//    def checkTreeNodes(node: IFNode, node2: IFNode): Unit = {
-//      (node, node2) match {
-//        case (node: IFInternalNode, node2: IFInternalNode) =>
-//          assert(node.featureValue === node2.featureValue)
-//          assert(node.featureIndex === node2.featureIndex)
-//          checkTreeNodes(node.leftChild, node2.leftChild)
-//          checkTreeNodes(node.rightChild, node2.rightChild)
-//        case (node: IFLeafNode, node2: IFLeafNode) =>
-//          assert(node.numInstance === node2.numInstance)
-//        case _ =>
-//          throw new AssertionError("Found mismatched nodes")
-//      }
-//    }
-//    def checkModelData(model: IForestModel, model2: IForestModel): Unit = {
-//      val trees = model.trees
-//      val trees2 = model2.trees
-//      assert(trees.length === trees2.length)
-//      try {
-//        trees.zip(trees2).foreach { case (node, node2) =>
-//          checkTreeNodes(node, node2)
-//        }
-//      } catch {
-//        case ex: Exception => throw new AssertionError(
-//          "checkModelData failed since the two trees were not identical.\n"
-//        )
-//      }
-//    }
-//
-//    val iforest = new IForest()
-//    testEstimatorAndModelReadWrite(
-//      iforest,
-//      dataset,
-//      IForestSuite.allParamSettings,
-//      IForestSuite.allParamSettings,
-//      checkModelData
-//    )
-//  }
+  // test for model read/write
+  test("read/write") {
+    def checkTreeNodes(node: IFNode, node2: IFNode): Unit = {
+      (node, node2) match {
+        case (node: IFInternalNode, node2: IFInternalNode) =>
+          assert(node.featureValue === node2.featureValue)
+          assert(node.featureIndex === node2.featureIndex)
+          checkTreeNodes(node.leftChild, node2.leftChild)
+          checkTreeNodes(node.rightChild, node2.rightChild)
+        case (node: IFLeafNode, node2: IFLeafNode) =>
+          assert(node.numInstance === node2.numInstance)
+        case _ =>
+          throw new AssertionError("Found mismatched nodes")
+      }
+    }
+    def checkModelData(model: IForestModel, model2: IForestModel): Unit = {
+      val trees = model.trees
+      val trees2 = model2.trees
+      assert(trees.length === trees2.length)
+      try {
+        trees.zip(trees2).foreach { case (node, node2) =>
+          checkTreeNodes(node, node2)
+        }
+      } catch {
+        case ex: Exception => throw new AssertionError(
+          "checkModelData failed since the two trees were not identical.\n"
+        )
+      }
+    }
+
+    val iforest = new IForest()
+    testEstimatorAndModelReadWrite(
+      iforest,
+      dataset,
+      IForestSuite.allParamSettings,
+      IForestSuite.allParamSettings,
+      checkModelData
+    )
+  }
 
   test("boundary case") {
     intercept[IllegalArgumentException] {