3 files changed, 21 insertions, 5 deletions
diff --git a/python/pyspark/ml/param/__init__.py b/python/pyspark/ml/param/__init__.py
index a1265294a1..9f0b063aac 100644
--- a/python/pyspark/ml/param/__init__.py
+++ b/python/pyspark/ml/param/__init__.py
@@ -26,6 +26,8 @@ import copy
 import numpy as np
 import warnings
 
+from py4j.java_gateway import JavaObject
+
 from pyspark import since
 from pyspark.ml.util import Identifiable
 from pyspark.mllib.linalg import DenseVector, Vector
@@ -389,8 +391,8 @@ class Params(Identifiable):
         if extra is None:
             extra = dict()
         that = copy.copy(self)
-        that._paramMap = self.extractParamMap(extra)
-        return that
+        that._paramMap = {}
+        return self._copyValues(that, extra)
 
     def _shouldOwn(self, param):
         """
@@ -439,12 +441,26 @@ class Params(Identifiable):
             self._paramMap[p] = value
         return self
 
+    def _clear(self, param):
+        """
+        Clears a param from the param map if it has been explicitly set.
+        """
+        if self.isSet(param):
+            del self._paramMap[param]
+
     def _setDefault(self, **kwargs):
         """
         Sets default params.
         """
         for param, value in kwargs.items():
-            self._defaultParamMap[getattr(self, param)] = value
+            p = getattr(self, param)
+            if value is not None and not isinstance(value, JavaObject):
+                try:
+                    value = p.typeConverter(value)
+                except TypeError as e:
+                    raise TypeError('Invalid default param value given for param "%s". %s'
+                                    % (p.name, e))
+            self._defaultParamMap[p] = value
         return self
 
     def _copyValues(self, to, extra=None):
diff --git a/python/pyspark/ml/param/_shared_params_code_gen.py b/python/pyspark/ml/param/_shared_params_code_gen.py
index a7615c43be..a2acf956bc 100644
--- a/python/pyspark/ml/param/_shared_params_code_gen.py
+++ b/python/pyspark/ml/param/_shared_params_code_gen.py
@@ -131,7 +131,7 @@ if __name__ == "__main__":
          "TypeConverters.toFloat"),
         ("handleInvalid", "how to handle invalid entries. Options are skip (which will filter " +
          "out rows with bad values), or error (which will throw an errror). More options may be " +
-         "added later.", None, "TypeConverters.toBoolean"),
+         "added later.", None, "TypeConverters.toString"),
         ("elasticNetParam", "the ElasticNet mixing parameter, in range [0, 1]. For alpha = 0, " +
          "the penalty is an L2 penalty. For alpha = 1, it is an L1 penalty.", "0.0",
          "TypeConverters.toFloat"),
diff --git a/python/pyspark/ml/param/shared.py b/python/pyspark/ml/param/shared.py
index c9e975525c..538c0b718a 100644
--- a/python/pyspark/ml/param/shared.py
+++ b/python/pyspark/ml/param/shared.py
@@ -392,7 +392,7 @@ class HasHandleInvalid(Params):
     Mixin for param handleInvalid: how to handle invalid entries. Options are skip (which will filter out rows with bad values), or error (which will throw an errror). More options may be added later.
     """
 
-    handleInvalid = Param(Params._dummy(), "handleInvalid", "how to handle invalid entries. Options are skip (which will filter out rows with bad values), or error (which will throw an errror). More options may be added later.", typeConverter=TypeConverters.toBoolean)
+    handleInvalid = Param(Params._dummy(), "handleInvalid", "how to handle invalid entries. Options are skip (which will filter out rows with bad values), or error (which will throw an errror). More options may be added later.", typeConverter=TypeConverters.toString)
 
     def __init__(self):
         super(HasHandleInvalid, self).__init__()