[SPARK-1406] Added PMMLExportable to supported models

selvinsource · Feb 8, 2015 · f46c75c · f46c75c
1 parent 7b33b4e
commit f46c75c
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Showing 6 changed files with 12 additions and 6 deletions.
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala b/mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala
@@ -23,6 +23,7 @@ import org.apache.spark.mllib.classification.impl.GLMClassificationModel
 import org.apache.spark.mllib.linalg.BLAS.dot
 import org.apache.spark.mllib.linalg.{DenseVector, Vector}
 import org.apache.spark.mllib.optimization._
+import org.apache.spark.mllib.pmml.PMMLExportable
 import org.apache.spark.mllib.regression._
 import org.apache.spark.mllib.util.{DataValidators, Saveable, Loader}
 import org.apache.spark.rdd.RDD
@@ -46,7 +47,7 @@ class LogisticRegressionModel (
     val numFeatures: Int,
     val numClasses: Int)
   extends GeneralizedLinearModel(weights, intercept) with ClassificationModel with Serializable
-  with Saveable {
+  with Saveable with PMMLExportable {
 
   if (numClasses == 2) {
     require(weights.size == numFeatures,

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/classification/SVM.scala b/mllib/src/main/scala/org/apache/spark/mllib/classification/SVM.scala
@@ -22,6 +22,7 @@ import org.apache.spark.annotation.Experimental
 import org.apache.spark.mllib.classification.impl.GLMClassificationModel
 import org.apache.spark.mllib.linalg.Vector
 import org.apache.spark.mllib.optimization._
+import org.apache.spark.mllib.pmml.PMMLExportable
 import org.apache.spark.mllib.regression._
 import org.apache.spark.mllib.util.{DataValidators, Saveable, Loader}
 import org.apache.spark.rdd.RDD
@@ -37,7 +38,7 @@ class SVMModel (
     override val weights: Vector,
     override val intercept: Double)
   extends GeneralizedLinearModel(weights, intercept) with ClassificationModel with Serializable
-  with Saveable {
+  with Saveable with PMMLExportable {
 
   private var threshold: Option[Double] = Some(0.0)
 

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeansModel.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeansModel.scala
@@ -21,11 +21,12 @@ import org.apache.spark.api.java.JavaRDD
 import org.apache.spark.rdd.RDD
 import org.apache.spark.SparkContext._
 import org.apache.spark.mllib.linalg.Vector
+import org.apache.spark.mllib.pmml.PMMLExportable
 
 /**
  * A clustering model for K-means. Each point belongs to the cluster with the closest center.
  */
-class KMeansModel (val clusterCenters: Array[Vector]) extends Serializable {
+class KMeansModel (val clusterCenters: Array[Vector]) extends Serializable with PMMLExportable {
 
   /** Total number of clusters. */
   def k: Int = clusterCenters.length

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/regression/Lasso.scala b/mllib/src/main/scala/org/apache/spark/mllib/regression/Lasso.scala
@@ -20,6 +20,7 @@ package org.apache.spark.mllib.regression
 import org.apache.spark.SparkContext
 import org.apache.spark.mllib.linalg.Vector
 import org.apache.spark.mllib.optimization._
+import org.apache.spark.mllib.pmml.PMMLExportable
 import org.apache.spark.mllib.regression.impl.GLMRegressionModel
 import org.apache.spark.mllib.util.{Saveable, Loader}
 import org.apache.spark.rdd.RDD
@@ -34,7 +35,7 @@ class LassoModel (
     override val weights: Vector,
     override val intercept: Double)
   extends GeneralizedLinearModel(weights, intercept)
-  with RegressionModel with Serializable with Saveable {
+  with RegressionModel with Serializable with Saveable with PMMLExportable {
 
   override protected def predictPoint(
       dataMatrix: Vector,

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/regression/LinearRegression.scala b/mllib/src/main/scala/org/apache/spark/mllib/regression/LinearRegression.scala
@@ -20,6 +20,7 @@ package org.apache.spark.mllib.regression
 import org.apache.spark.SparkContext
 import org.apache.spark.mllib.linalg.Vector
 import org.apache.spark.mllib.optimization._
+import org.apache.spark.mllib.pmml.PMMLExportable
 import org.apache.spark.mllib.regression.impl.GLMRegressionModel
 import org.apache.spark.mllib.util.{Saveable, Loader}
 import org.apache.spark.rdd.RDD
@@ -34,7 +35,7 @@ class LinearRegressionModel (
     override val weights: Vector,
     override val intercept: Double)
   extends GeneralizedLinearModel(weights, intercept) with RegressionModel with Serializable
-  with Saveable {
+  with Saveable with PMMLExportable {
 
   override protected def predictPoint(
       dataMatrix: Vector,

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/regression/RidgeRegression.scala b/mllib/src/main/scala/org/apache/spark/mllib/regression/RidgeRegression.scala
@@ -20,6 +20,7 @@ package org.apache.spark.mllib.regression
 import org.apache.spark.SparkContext
 import org.apache.spark.mllib.linalg.Vector
 import org.apache.spark.mllib.optimization._
+import org.apache.spark.mllib.pmml.PMMLExportable
 import org.apache.spark.mllib.regression.impl.GLMRegressionModel
 import org.apache.spark.mllib.util.{Loader, Saveable}
 import org.apache.spark.rdd.RDD
@@ -35,7 +36,7 @@ class RidgeRegressionModel (
     override val weights: Vector,
     override val intercept: Double)
   extends GeneralizedLinearModel(weights, intercept)
-  with RegressionModel with Serializable with Saveable {
+  with RegressionModel with Serializable with Saveable with PMMLExportable {
 
   override protected def predictPoint(
       dataMatrix: Vector,