[SPARK-8069] [ML] Add multiclass thresholds for ProbabilisticClassifier

This PR replaces the old "threshold" with a generalized "thresholds" Param.  We keep getThreshold,setThreshold for backwards compatibility for binary classification.

Note that the primary author of this PR is holdenk

Author: Holden Karau <holden@pigscanfly.ca>
Author: Joseph K. Bradley <joseph@databricks.com>

Closes #7909 from jkbradley/holdenk-SPARK-8069-add-cutoff-aka-threshold-to-random-forest and squashes the following commits:

3952977 [Joseph K. Bradley] fixed pyspark doc test
85febc8 [Joseph K. Bradley] made python unit tests a little more robust
7eb1d86 [Joseph K. Bradley] small cleanups
6cc2ed8 [Joseph K. Bradley] Fixed remaining merge issues.
0255e44 [Joseph K. Bradley] Many cleanups for thresholds, some more tests
7565a60 [Holden Karau] fix pep8 style checks, add a getThreshold method similar to our LogisticRegression.scala one for API compat
be87f26 [Holden Karau] Convert threshold to thresholds in the python code, add specialized support for Array[Double] to shared parems codegen, etc.
6747dad [Holden Karau] Override raw2prediction for ProbabilisticClassifier, fix some tests
25df168 [Holden Karau] Fix handling of thresholds in LogisticRegression
c02d6c0 [Holden Karau] No default for thresholds
5e43628 [Holden Karau] CR feedback and fixed the renamed test
f3fbbd1 [Holden Karau] revert the changes to random forest :(
51f581c [Holden Karau] Add explicit types to public methods, fix long line
f7032eb [Holden Karau] Fix a java test bug, remove some unecessary changes
adf15b4 [Holden Karau] rename the classifier suite test to ProbabilisticClassifierSuite now that we only have it in Probabilistic
398078a [Holden Karau] move the thresholding around a bunch based on the design doc
4893bdc [Holden Karau] Use numtrees of 3 since previous result was tied (one tree for each) and the switch from different max methods picked a different element (since they were equal I think this is ok)
638854c [Holden Karau] Add a scala RandomForestClassifierSuite test based on corresponding python test
e09919c [Holden Karau] Fix return type, I need more coffee....
8d92cac [Holden Karau] Use ClassifierParams as the head
3456ed3 [Holden Karau] Add explicit return types even though just test
a0f3b0c [Holden Karau] scala style fixes
6f14314 [Holden Karau] Since hasthreshold/hasthresholds is in root classifier now
ffc8dab [Holden Karau] Update the sharedParams
0420290 [Holden Karau] Allow us to override the get methods selectively
978e77a [Holden Karau] Move HasThreshold into classifier params and start defining the overloaded getThreshold/getThresholds functions
1433e52 [Holden Karau] Revert "try and hide threshold but chainges the API so no dice there"
1f09a2e [Holden Karau] try and hide threshold but chainges the API so no dice there
efb9084 [Holden Karau] move setThresholds only to where its used
6b34809 [Holden Karau] Add a test with thresholding for the RFCS
74f54c3 [Holden Karau] Fix creation of vote array
1986fa8 [Holden Karau] Setting the thresholds only makes sense if the underlying class hasn't overridden predict, so lets push it down.
2f44b18 [Holden Karau] Add a global default of null for thresholds param
f338cfc [Holden Karau] Wait that wasn't a good idea, Revert "Some progress towards unifying threshold and thresholds"
634b06f [Holden Karau] Some progress towards unifying threshold and thresholds
85c9e01 [Holden Karau] Test passes again... little fnur
099c0f3 [Holden Karau] Move thresholds around some more (set on model not trainer)
0f46836 [Holden Karau] Start adding a classifiersuite
f70eb5e [Holden Karau] Fix test compile issues
a7d59c8 [Holden Karau] Move thresholding into Classifier trait
5d999d2 [Holden Karau] Some more progress, start adding a test (maybe try and see if we can find a better thing to use for the base of the test)
1fed644 [Holden Karau] Use thresholds to scale scores in random forest classifcation
31d6bf2 [Holden Karau] Start threading the threshold info through
0ef228c [Holden Karau] Add hasthresholds

1 files changed, 7 insertions, 2 deletions

diff --git a/mllib/src/test/java/org/apache/spark/ml/classification/JavaLogisticRegressionSuite.java b/mllib/src/test/java/org/apache/spark/ml/classification/JavaLogisticRegressionSuite.java
index f75e024a71..fb1de51163 100644
--- a/mllib/src/test/java/org/apache/spark/ml/classification/JavaLogisticRegressionSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/classification/JavaLogisticRegressionSuite.java
@@ -87,6 +87,8 @@ public class JavaLogisticRegressionSuite implements Serializable {
     LogisticRegression parent = (LogisticRegression) model.parent();
     assert(parent.getMaxIter() == 10);
     assert(parent.getRegParam() == 1.0);
+    assert(parent.getThresholds()[0] == 0.4);
+    assert(parent.getThresholds()[1] == 0.6);
     assert(parent.getThreshold() == 0.6);
     assert(model.getThreshold() == 0.6);
 
@@ -98,7 +100,9 @@ public class JavaLogisticRegressionSuite implements Serializable {
       assert(r.getDouble(0) == 0.0);
     }
     // Call transform with params, and check that the params worked.
-    model.transform(dataset, model.threshold().w(0.0), model.probabilityCol().w("myProb"))
+    double[] thresholds = {1.0, 0.0};
+    model.transform(
+      dataset, model.thresholds().w(thresholds), model.probabilityCol().w("myProb"))
       .registerTempTable("predNotAllZero");
     DataFrame predNotAllZero = jsql.sql("SELECT prediction, myProb FROM predNotAllZero");
     boolean foundNonZero = false;
@@ -108,8 +112,9 @@ public class JavaLogisticRegressionSuite implements Serializable {
     assert(foundNonZero);
 
     // Call fit() with new params, and check as many params as we can.
+    double[] thresholds2 = {0.6, 0.4};
     LogisticRegressionModel model2 = lr.fit(dataset, lr.maxIter().w(5), lr.regParam().w(0.1),
-        lr.threshold().w(0.4), lr.probabilityCol().w("theProb"));
+        lr.thresholds().w(thresholds2), lr.probabilityCol().w("theProb"));
     LogisticRegression parent2 = (LogisticRegression) model2.parent();
     assert(parent2.getMaxIter() == 5);
     assert(parent2.getRegParam() == 0.1);