[SPARK-9909] [ML] [TRIVIAL] move weightCol to shared params

As per the TODO move weightCol to Shared Params.

Author: Holden Karau <holden@pigscanfly.ca>

Closes #8144 from holdenk/SPARK-9909-move-weightCol-toSharedParams.

3 files changed, 20 insertions, 15 deletions

diff --git a/mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala b/mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala
index 9e12f1856a..8c16c6149b 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/param/shared/SharedParamsCodeGen.scala
@@ -70,7 +70,9 @@ private[shared] object SharedParamsCodeGen {
         " For alpha = 0, the penalty is an L2 penalty. For alpha = 1, it is an L1 penalty.",
         isValid = "ParamValidators.inRange(0, 1)"),
       ParamDesc[Double]("tol", "the convergence tolerance for iterative algorithms"),
-      ParamDesc[Double]("stepSize", "Step size to be used for each iteration of optimization."))
+      ParamDesc[Double]("stepSize", "Step size to be used for each iteration of optimization."),
+      ParamDesc[String]("weightCol", "weight column name. If this is not set or empty, we treat " +
+        "all instance weights as 1.0."))
 
     val code = genSharedParams(params)
     val file = "src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala"
diff --git a/mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala b/mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala
index a17d4ea960..c26768953e 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/param/shared/sharedParams.scala
@@ -342,4 +342,19 @@ private[ml] trait HasStepSize extends Params {
   /** @group getParam */
   final def getStepSize: Double = $(stepSize)
 }
+
+/**
+ * Trait for shared param weightCol.
+ */
+private[ml] trait HasWeightCol extends Params {
+
+  /**
+   * Param for weight column name. If this is not set or empty, we treat all instance weights as 1.0..
+   * @group param
+   */
+  final val weightCol: Param[String] = new Param[String](this, "weightCol", "weight column name. If this is not set or empty, we treat all instance weights as 1.0.")
+
+  /** @group getParam */
+  final def getWeightCol: String = $(weightCol)
+}
 // scalastyle:on
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/IsotonicRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/IsotonicRegression.scala
index f570590960..0f33bae30e 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/IsotonicRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/IsotonicRegression.scala
@@ -21,7 +21,7 @@ import org.apache.spark.Logging
 import org.apache.spark.annotation.Experimental
 import org.apache.spark.ml.{Estimator, Model}
 import org.apache.spark.ml.param._
-import org.apache.spark.ml.param.shared.{HasFeaturesCol, HasLabelCol, HasPredictionCol}
+import org.apache.spark.ml.param.shared.{HasFeaturesCol, HasLabelCol, HasPredictionCol, HasWeightCol}
 import org.apache.spark.ml.util.{Identifiable, SchemaUtils}
 import org.apache.spark.mllib.linalg.{Vector, VectorUDT, Vectors}
 import org.apache.spark.mllib.regression.{IsotonicRegression => MLlibIsotonicRegression, IsotonicRegressionModel => MLlibIsotonicRegressionModel}
@@ -35,19 +35,7 @@ import org.apache.spark.storage.StorageLevel
  * Params for isotonic regression.
  */
 private[regression] trait IsotonicRegressionBase extends Params with HasFeaturesCol
-  with HasLabelCol with HasPredictionCol with Logging {
-
-  /**
-   * Param for weight column name (default: none).
-   * @group param
-   */
-  // TODO: Move weightCol to sharedParams.
-  final val weightCol: Param[String] =
-    new Param[String](this, "weightCol",
-      "weight column name. If this is not set or empty, we treat all instance weights as 1.0.")
-
-  /** @group getParam */
-  final def getWeightCol: String = $(weightCol)
+  with HasLabelCol with HasPredictionCol with HasWeightCol with Logging {
 
   /**
    * Param for whether the output sequence should be isotonic/increasing (true) or