[SPARK-5957][ML] better handling of parameters

The design doc was posted on the JIRA page. Python changes will be in a follow-up PR. jkbradley

1. Use codegen for shared params.
1. Move shared params to package `ml.param.shared`.
1. Set default values in `Params` instead of in `Param`.
1. Add a few methods to `Params` and `ParamMap`.
1. Move schema handling to `SchemaUtils` from `Params`.

- [x] check visibility of the methods added

Author: Xiangrui Meng <meng@databricks.com>

Closes #5431 from mengxr/SPARK-5957 and squashes the following commits:

d19236d [Xiangrui Meng] fix test
26ae2d7 [Xiangrui Meng] re-gen code and mark clear protected
38b78c7 [Xiangrui Meng] update Param.toString and remove Params.explain()
409e2d5 [Xiangrui Meng] address comments
2d637bd [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-5957
eec2264 [Xiangrui Meng] make get* public in Params
4090d95 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-5957
4fee9e7 [Xiangrui Meng] re-gen shared params
2737c2d [Xiangrui Meng] rename SharedParamCodeGen to SharedParamsCodeGen
e938f81 [Xiangrui Meng] update code to set default parameter values
28ed322 [Xiangrui Meng] merge master
55be1f3 [Xiangrui Meng] merge master
d63b5cc [Xiangrui Meng] fix examples
29b004c [Xiangrui Meng] update ParamsSuite
94fd98e [Xiangrui Meng] fix explain params
48d0e84 [Xiangrui Meng] add remove and update explainParams
4ac6348 [Xiangrui Meng] move schema utils to SchemaUtils add a few methods to Params
0d9594e [Xiangrui Meng] add getOrElse to ParamMap
eeeffe8 [Xiangrui Meng] map ++ paramMap => extractValues
0d3fc5b [Xiangrui Meng] setDefault after param
a9dbf59 [Xiangrui Meng] minor updates
d9302b8 [Xiangrui Meng] generate default values
1c72579 [Xiangrui Meng] pass test compile
abb7a3b [Xiangrui Meng] update default values handling
dcab97a [Xiangrui Meng] add codegen for shared params

2 files changed, 5 insertions, 5 deletions

diff --git a/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java b/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java
index 19d0eb2168..eaf00d09f5 100644
--- a/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java
+++ b/examples/src/main/java/org/apache/spark/examples/ml/JavaDeveloperApiExample.java
@@ -116,7 +116,7 @@ class MyJavaLogisticRegression
    */
   IntParam maxIter = new IntParam(this, "maxIter", "max number of iterations");
 
-  int getMaxIter() { return (Integer) get(maxIter); }
+  int getMaxIter() { return (Integer) getOrDefault(maxIter); }
 
   public MyJavaLogisticRegression() {
     setMaxIter(100);
@@ -211,7 +211,7 @@ class MyJavaLogisticRegressionModel
   public MyJavaLogisticRegressionModel copy() {
     MyJavaLogisticRegressionModel m =
         new MyJavaLogisticRegressionModel(parent_, fittingParamMap_, weights_);
-    Params$.MODULE$.inheritValues(this.paramMap(), this, m);
+    Params$.MODULE$.inheritValues(this.extractParamMap(), this, m);
     return m;
   }
 }
diff --git a/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala b/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala
index df26798e41..2245fa429f 100644
--- a/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/ml/DeveloperApiExample.scala
@@ -99,7 +99,7 @@ private trait MyLogisticRegressionParams extends ClassifierParams {
    * class since the maxIter parameter is only used during training (not in the Model).
    */
   val maxIter: IntParam = new IntParam(this, "maxIter", "max number of iterations")
-  def getMaxIter: Int = get(maxIter)
+  def getMaxIter: Int = getOrDefault(maxIter)
 }
 
 /**
@@ -174,11 +174,11 @@ private class MyLogisticRegressionModel(
    * Create a copy of the model.
    * The copy is shallow, except for the embedded paramMap, which gets a deep copy.
    *
-   * This is used for the defaul implementation of [[transform()]].
+   * This is used for the default implementation of [[transform()]].
    */
   override protected def copy(): MyLogisticRegressionModel = {
     val m = new MyLogisticRegressionModel(parent, fittingParamMap, weights)
-    Params.inheritValues(this.paramMap, this, m)
+    Params.inheritValues(extractParamMap(), this, m)
     m
   }
 }