Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/4233#discussion_r24054680
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala
---
@@ -17,14 +17,17 @@
package org.apache.spark.mllib.classification
+import org.apache.spark.SparkContext
import org.apache.spark.annotation.Experimental
+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.regression._
-import org.apache.spark.mllib.util.{DataValidators, MLUtils}
+import org.apache.spark.mllib.util.{DataValidators, Exportable, Importable}
--- End diff --
Saveable and Loader sound good to me. What about PMML? Does it sounds
reasonable to have separate traits for PMML such as PMMLSaveable and
PMMLLoadable?
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