[SPARK-1406] Update code to latest pmml model

Author: selvinsource

mllib/src/main/scala/org/apache/spark/mllib/pmml/export/GeneralizedLinearPMMLModelExport.scala

@@ -44,7 +44,9 @@ private[mllib] class GeneralizedLinearPMMLModelExport(
       val dataDictionary = new DataDictionary
       val miningSchema = new MiningSchema
       val regressionTable = new RegressionTable(model.intercept)
-      val regressionModel = new RegressionModel(miningSchema, MiningFunctionType.REGRESSION)
+      val regressionModel = new RegressionModel()
+        .withFunctionName(MiningFunctionType.REGRESSION)
+        .withMiningSchema(miningSchema)
         .withModelName(description)
         .withRegressionTables(regressionTable)
 

mllib/src/main/scala/org/apache/spark/mllib/pmml/export/KMeansPMMLModelExport.scala

@@ -44,10 +44,13 @@ private[mllib] class KMeansPMMLModelExport(model : KMeansModel) extends PMMLMode
       val comparisonMeasure = new ComparisonMeasure()
         .withKind(ComparisonMeasure.Kind.DISTANCE)
         .withMeasure(new SquaredEuclidean())
-      val clusteringModel = new ClusteringModel(miningSchema, comparisonMeasure,
-          MiningFunctionType.CLUSTERING, ClusteringModel.ModelClass.CENTER_BASED,
-          model.clusterCenters.length)
+      val clusteringModel = new ClusteringModel()
         .withModelName("k-means")
+        .withMiningSchema(miningSchema)
+        .withComparisonMeasure(comparisonMeasure)
+        .withFunctionName(MiningFunctionType.CLUSTERING)
+        .withModelClass(ClusteringModel.ModelClass.CENTER_BASED)
+        .withNumberOfClusters(model.clusterCenters.length)
 
       for (i <- 0 until clusterCenter.size) {
         fields(i) = FieldName.create("field_" + i)

mllib/src/main/scala/org/apache/spark/mllib/pmml/export/LogisticRegressionPMMLModelExport.scala

@@ -45,7 +45,9 @@ private[mllib] class LogisticRegressionPMMLModelExport(
        val miningSchema = new MiningSchema
        val regressionTableYES = new RegressionTable(model.intercept).withTargetCategory("1")
        val regressionTableNO = new RegressionTable(0.0).withTargetCategory("0")
-       val regressionModel = new RegressionModel(miningSchema, MiningFunctionType.CLASSIFICATION)
+       val regressionModel = new RegressionModel()
+         .withFunctionName(MiningFunctionType.CLASSIFICATION)
+         .withMiningSchema(miningSchema)
          .withModelName(description)
          .withNormalizationMethod(RegressionNormalizationMethodType.LOGIT)
          .withRegressionTables(regressionTableYES, regressionTableNO)