1 files changed, 14 insertions, 15 deletions

diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
index 71c2533bcb..a3cc49f7f0 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
@@ -29,9 +29,9 @@ import org.apache.spark.ml.feature.Instance
 import org.apache.spark.ml.param._
 import org.apache.spark.ml.param.shared._
 import org.apache.spark.ml.util._
+import org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
 import org.apache.spark.mllib.linalg._
 import org.apache.spark.mllib.linalg.BLAS._
-import org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
 import org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
 import org.apache.spark.mllib.util.MLUtils
 import org.apache.spark.rdd.RDD
@@ -157,7 +157,7 @@ private[classification] trait LogisticRegressionParams extends ProbabilisticClas
 @Experimental
 class LogisticRegression(override val uid: String)
   extends ProbabilisticClassifier[Vector, LogisticRegression, LogisticRegressionModel]
-  with LogisticRegressionParams with Writable with Logging {
+  with LogisticRegressionParams with DefaultParamsWritable with Logging {
 
   def this() = this(Identifiable.randomUID("logreg"))
 
@@ -385,12 +385,11 @@ class LogisticRegression(override val uid: String)
   }
 
   override def copy(extra: ParamMap): LogisticRegression = defaultCopy(extra)
-
-  override def write: Writer = new DefaultParamsWriter(this)
 }
 
-object LogisticRegression extends Readable[LogisticRegression] {
-  override def read: Reader[LogisticRegression] = new DefaultParamsReader[LogisticRegression]
+object LogisticRegression extends DefaultParamsReadable[LogisticRegression] {
+
+  override def load(path: String): LogisticRegression = super.load(path)
 }
 
 /**
@@ -403,7 +402,7 @@ class LogisticRegressionModel private[ml] (
     val coefficients: Vector,
     val intercept: Double)
   extends ProbabilisticClassificationModel[Vector, LogisticRegressionModel]
-  with LogisticRegressionParams with Writable {
+  with LogisticRegressionParams with MLWritable {
 
   @deprecated("Use coefficients instead.", "1.6.0")
   def weights: Vector = coefficients
@@ -519,26 +518,26 @@ class LogisticRegressionModel private[ml] (
   }
 
   /**
-   * Returns a [[Writer]] instance for this ML instance.
+   * Returns a [[MLWriter]] instance for this ML instance.
    *
    * For [[LogisticRegressionModel]], this does NOT currently save the training [[summary]].
    * An option to save [[summary]] may be added in the future.
    *
    * This also does not save the [[parent]] currently.
    */
-  override def write: Writer = new LogisticRegressionModel.LogisticRegressionModelWriter(this)
+  override def write: MLWriter = new LogisticRegressionModel.LogisticRegressionModelWriter(this)
 }
 
 
-object LogisticRegressionModel extends Readable[LogisticRegressionModel] {
+object LogisticRegressionModel extends MLReadable[LogisticRegressionModel] {
 
-  override def read: Reader[LogisticRegressionModel] = new LogisticRegressionModelReader
+  override def read: MLReader[LogisticRegressionModel] = new LogisticRegressionModelReader
 
-  override def load(path: String): LogisticRegressionModel = read.load(path)
+  override def load(path: String): LogisticRegressionModel = super.load(path)
 
-  /** [[Writer]] instance for [[LogisticRegressionModel]] */
+  /** [[MLWriter]] instance for [[LogisticRegressionModel]] */
   private[classification] class LogisticRegressionModelWriter(instance: LogisticRegressionModel)
-    extends Writer with Logging {
+    extends MLWriter with Logging {
 
     private case class Data(
         numClasses: Int,
@@ -558,7 +557,7 @@ object LogisticRegressionModel extends Readable[LogisticRegressionModel] {
   }
 
   private[classification] class LogisticRegressionModelReader
-    extends Reader[LogisticRegressionModel] {
+    extends MLReader[LogisticRegressionModel] {
 
     /** Checked against metadata when loading model */
     private val className = "org.apache.spark.ml.classification.LogisticRegressionModel"