[SPARK-7547] [ML] Scala Example code for ElasticNet

This is scala example code for both linear and logistic regression. Python and Java versions are to be added.

Author: DB Tsai <dbt@netflix.com>

Closes #6576 from dbtsai/elasticNetExample and squashes the following commits:

e7ca406 [DB Tsai] fix test
6bb6d77 [DB Tsai] fix suite and remove duplicated setMaxIter
136e0dd [DB Tsai] address feedback
1ec29d4 [DB Tsai] fix style
9462f5f [DB Tsai] add example

5 files changed, 13 insertions, 9 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 d13109d9da..f136bcee9c 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
@@ -74,7 +74,7 @@ class LogisticRegression(override val uid: String)
   setDefault(elasticNetParam -> 0.0)
 
   /**
-   * Set the maximal number of iterations.
+   * Set the maximum number of iterations.
    * Default is 100.
    * @group setParam
    */
@@ -90,7 +90,11 @@ class LogisticRegression(override val uid: String)
   def setTol(value: Double): this.type = set(tol, value)
   setDefault(tol -> 1E-6)
 
-  /** @group setParam */
+  /**
+   * Whether to fit an intercept term.
+   * Default is true.
+   * @group setParam
+   * */
   def setFitIntercept(value: Boolean): this.type = set(fitIntercept, value)
   setDefault(fitIntercept -> true)
 
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 1ffb5eddc3..8ffbcf0d8b 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
@@ -33,7 +33,7 @@ private[shared] object SharedParamsCodeGen {
     val params = Seq(
       ParamDesc[Double]("regParam", "regularization parameter (>= 0)",
         isValid = "ParamValidators.gtEq(0)"),
-      ParamDesc[Int]("maxIter", "max number of iterations (>= 0)",
+      ParamDesc[Int]("maxIter", "maximum number of iterations (>= 0)",
         isValid = "ParamValidators.gtEq(0)"),
       ParamDesc[String]("featuresCol", "features column name", Some("\"features\"")),
       ParamDesc[String]("labelCol", "label column name", Some("\"label\"")),
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 ed08417bd4..a0c8ccdac9 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
@@ -45,10 +45,10 @@ private[ml] trait HasRegParam extends Params {
 private[ml] trait HasMaxIter extends Params {
 
   /**
-   * Param for max number of iterations (>= 0).
+   * Param for maximum number of iterations (>= 0).
    * @group param
    */
-  final val maxIter: IntParam = new IntParam(this, "maxIter", "max number of iterations (>= 0)", ParamValidators.gtEq(0))
+  final val maxIter: IntParam = new IntParam(this, "maxIter", "maximum number of iterations (>= 0)", ParamValidators.gtEq(0))
 
   /** @group getParam */
   final def getMaxIter: Int = $(maxIter)
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
index fe2a71a331..70cd8e9e87 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
@@ -83,7 +83,7 @@ class LinearRegression(override val uid: String)
   setDefault(elasticNetParam -> 0.0)
 
   /**
-   * Set the maximal number of iterations.
+   * Set the maximum number of iterations.
    * Default is 100.
    * @group setParam
    */
diff --git a/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala
index f80e774909..96094d7a09 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala
@@ -27,7 +27,7 @@ class ParamsSuite extends SparkFunSuite {
     import solver.{maxIter, inputCol}
 
     assert(maxIter.name === "maxIter")
-    assert(maxIter.doc === "max number of iterations (>= 0)")
+    assert(maxIter.doc === "maximum number of iterations (>= 0)")
     assert(maxIter.parent === uid)
     assert(maxIter.toString === s"${uid}__maxIter")
     assert(!maxIter.isValid(-1))
@@ -36,7 +36,7 @@ class ParamsSuite extends SparkFunSuite {
 
     solver.setMaxIter(5)
     assert(solver.explainParam(maxIter) ===
-      "maxIter: max number of iterations (>= 0) (default: 10, current: 5)")
+      "maxIter: maximum number of iterations (>= 0) (default: 10, current: 5)")
 
     assert(inputCol.toString === s"${uid}__inputCol")
 
@@ -120,7 +120,7 @@ class ParamsSuite extends SparkFunSuite {
     intercept[NoSuchElementException](solver.getInputCol)
 
     assert(solver.explainParam(maxIter) ===
-      "maxIter: max number of iterations (>= 0) (default: 10, current: 100)")
+      "maxIter: maximum number of iterations (>= 0) (default: 10, current: 100)")
     assert(solver.explainParams() ===
       Seq(inputCol, maxIter).map(solver.explainParam).mkString("\n"))