Move implicit arg to constructor for Java access.

1 files changed, 7 insertions, 4 deletions

diff --git a/mllib/src/main/scala/spark/mllib/regression/GeneralizedLinearAlgorithm.scala b/mllib/src/main/scala/spark/mllib/regression/GeneralizedLinearAlgorithm.scala
index 0bbc9424e6..7e80737773 100644
--- a/mllib/src/main/scala/spark/mllib/regression/GeneralizedLinearAlgorithm.scala
+++ b/mllib/src/main/scala/spark/mllib/regression/GeneralizedLinearAlgorithm.scala
@@ -66,7 +66,10 @@ abstract class GeneralizedLinearModel[T: ClassManifest](
  * NOTE(shivaram): This is an abstract class rather than a trait as we use
  * a view bound to convert labels to Double.
  */
-abstract class GeneralizedLinearAlgorithm[T <% Double, M <: GeneralizedLinearModel[T]]
+abstract class GeneralizedLinearAlgorithm[T, M](implicit
+    t: T => Double,
+    tManifest: Manifest[T],
+    methodEv: M <:< GeneralizedLinearModel[T])
   extends Logging with Serializable {
 
   // We need an optimizer mixin to solve the GLM
@@ -84,15 +87,15 @@ abstract class GeneralizedLinearAlgorithm[T <% Double, M <: GeneralizedLinearMod
     this
   }
 
-  def train(input: RDD[(T, Array[Double])])(implicit mt: Manifest[T]) : M = {
-    val nfeatures: Int = input.take(1)(0)._2.length
+  def train(input: RDD[(T, Array[Double])]) : M = {
+    val nfeatures: Int = input.first()._2.length
     val initialWeights = Array.fill(nfeatures)(1.0)
     train(input, initialWeights)
   }
 
   def train(
       input: RDD[(T, Array[Double])],
-      initialWeights: Array[Double])(implicit mt: Manifest[T])
+      initialWeights: Array[Double])
     : M = {
 
     // Add a extra variable consisting of all 1.0's for the intercept.