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From yinxusen <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-8542][MLlib]PMML export for Decision Tr...
Date Wed, 28 Oct 2015 02:37:30 GMT
Github user yinxusen commented on a diff in the pull request:

    https://github.com/apache/spark/pull/7842#discussion_r43213272
  
    --- Diff: mllib/src/main/scala/org/apache/spark/mllib/pmml/export/PMMLTreeModelUtils.scala
---
    @@ -0,0 +1,282 @@
    +/*
    + * 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.pmml.export
    +
    +import scala.collection.mutable
    +import scala.collection.JavaConverters._
    +import scala.collection.mutable.MutableList
    +
    +import org.dmg.pmml.{Node => PMMLNode, Value => PMMLValue, _}
    +
    +import org.apache.spark.mllib.tree.configuration.{Algo, FeatureType}
    +import org.apache.spark.mllib.tree.configuration.Algo._
    +import org.apache.spark.mllib.tree.model.{DecisionTreeModel, Node}
    +
    +private[mllib] object PMMLTreeModelUtils {
    +
    +  val FieldNamePrefix = "field_"
    +
    +  def toPMMLTree(dtModel: DecisionTreeModel, modelName: String): (TreeModel, List[DataField])
= {
    +
    +    val miningFunctionType = getPMMLMiningFunctionType(dtModel.algo)
    +
    +    val treeModel = new org.dmg.pmml.TreeModel()
    +      .withModelName(modelName)
    +      .withFunctionName(miningFunctionType)
    +      .withSplitCharacteristic(TreeModel.SplitCharacteristic.BINARY_SPLIT)
    +
    +    var (rootNode, miningFields, dataFields, classes) = buildStub(dtModel.topNode, dtModel.algo)
    +
    +    // adding predicted classes for classification and target field for regression
    +    // for completeness
    +    dtModel.algo match {
    +
    +      case Algo.Classification => {
    +        miningFields = miningFields :+ new MiningField()
    +          .withName(FieldName.create("class"))
    +          .withUsageType(FieldUsageType.PREDICTED)
    +
    +        val dataField = new DataField()
    +          .withName(FieldName.create("class"))
    +          .withOpType(OpType.CATEGORICAL)
    +          .withValues(classes.asJava)
    +          .withDataType(DataType.DOUBLE)
    +
    +        dataFields = dataFields :+ dataField
    +      }
    +      case Algo.Regression => {
    +        val targetField = FieldName.create("target")
    +        val dataField = new DataField(targetField, OpType.CONTINUOUS, DataType.DOUBLE)
    +        dataFields = dataFields :+ dataField
    +
    +        miningFields = miningFields :+ new MiningField()
    +          .withName(targetField)
    +          .withUsageType(FieldUsageType.TARGET)
    +      }
    +    }
    +
    +    val miningSchema = new MiningSchema()
    +      .withMiningFields(miningFields.asJava)
    +
    +    treeModel.withNode(rootNode)
    +      .withMiningSchema(miningSchema)
    +
    +    (treeModel, dataFields)
    +
    +  }
    +
    +  /** Build a pmml tree stub given the root mllib node. */
    +  private def buildStub(
    +              rootDTNode: Node,
    +              algo: Algo): (PMMLNode, List[MiningField], List[DataField], List[PMMLValue])
= {
    +
    +    val miningFields = MutableList[MiningField]()
    +    val dataFields = mutable.HashMap[String, DataField]()
    +    val classes = mutable.MutableList[Double]()
    +
    +    def buildStubInternal(rootNode: Node, predicate: Predicate): PMMLNode = {
    +
    +      // get rootPMML node for the MLLib node
    +      val rootPMMLNode = createNode(rootNode)
    +      rootPMMLNode.withPredicate(predicate)
    +
    +      var leftPredicate: Predicate = new True()
    +      var rightPredicate: Predicate = new True()
    +
    +      if (rootNode.split.isDefined) {
    +        val fieldName = FieldName.create(FieldNamePrefix + rootNode.split.get.feature)
    +        val dataField = getDataField(rootNode, fieldName).get
    +
    +        if (!dataFields.get(dataField.getName.getValue).isDefined) {
    +          dataFields.put(dataField.getName.getValue, dataField)
    +          miningFields += new MiningField()
    +            .withName(dataField.getName)
    +            .withUsageType(FieldUsageType.ACTIVE)
    +
    +        } else if (dataField.getOpType != OpType.CONTINUOUS.value()) {
    +          appendCategories(
    +            dataFields.get(dataField.getName.getValue).get,
    +            dataField.getValues.asScala.toList)
    +        }
    +
    +        leftPredicate = getPredicate(rootNode, Some(dataField.getName), true)
    +        rightPredicate = getPredicate(rootNode, Some(dataField.getName), false)
    +
    +      }
    +      // if left node exist, add the node
    +      if (rootNode.leftNode.isDefined) {
    +        val leftNode = buildStubInternal(rootNode.leftNode.get, leftPredicate)
    +        rootPMMLNode.withNodes(leftNode)
    +      }
    +      // if right node exist, add the node
    +      if (rootNode.rightNode.isDefined) {
    +        val rightNode = buildStubInternal(rootNode.rightNode.get, rightPredicate)
    +        rootPMMLNode.withNodes(rightNode)
    +      }
    +
    +      // add to the list of classes
    +      if (rootNode.isLeaf && (algo == Algo.Classification)) {
    +        classes += rootNode.predict.predict
    +      }
    +
    +      rootPMMLNode
    +    }
    +
    +    val pmmlTreeRootNode = buildStubInternal(rootDTNode, new True())
    +
    +    val pmmlValues = classes.toList.distinct.map(doubleVal => new PMMLValue(doubleVal.toString))
    +
    +    val result = (pmmlTreeRootNode,
    +      sortMiningFields(miningFields.toList),
    +      sortedDataFields(dataFields.values.toList),
    +      pmmlValues)
    +
    +    result
    +
    +  }
    +
    +  private def sortMiningFields(miningFields: List[MiningField]): List[MiningField] =
{
    +    miningFields
    +      .sortBy { case mField => mField.getName.getValue.replace(FieldNamePrefix, "").toInt
}
    +  }
    +
    +  private def sortedDataFields(dataFields: List[DataField]): List[DataField] = {
    +    dataFields.sortBy { case dField => dField.getName.getValue.replace(FieldNamePrefix,
"").toInt }
    +  }
    +
    +  private def appendCategories(dtField: DataField, values: List[PMMLValue]): DataField
= {
    +    if (dtField.getOpType == OpType.CATEGORICAL) {
    +
    +      val existingValues = dtField.getValues.asScala
    +        .groupBy { case category => category.getValue }.toMap
    +
    +      values.foreach(category => {
    +        if (!existingValues.get(category.getValue).isDefined) {
    +          dtField.withValues(category)
    +        }
    +      })
    +    }
    +
    +    dtField
    +  }
    +
    +  /** Get pmml Predicate for a given mlLib tree node. */
    +  private def getPredicate(node: Node, fieldName: Option[FieldName], isLeft: Boolean):
Predicate = {
    +    // compound predicate if classification and categories list length > 0
    +
    +    if (node.split.isDefined) {
    +
    +      require(fieldName.isDefined, "fieldName should not be None, it should be defined.")
    +      val field = fieldName.get
    +
    +      val split = node.split.get
    +      val featureType = split.featureType
    +
    +      featureType match {
    +        case FeatureType.Continuous => {
    --- End diff --
    
    redundant curly braces


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