[SPARK-4586][MLLIB] Python API for ML pipeline and parameters

This PR adds Python API for ML pipeline and parameters. The design doc can be found on the JIRA page. It includes transformers and an estimator to demo the simple text classification example code.

TODO:
- [x] handle parameters in LRModel
- [x] unit tests
- [x] missing some docs

CC: davies jkbradley

Author: Xiangrui Meng <meng@databricks.com>
Author: Davies Liu <davies@databricks.com>

Closes #4151 from mengxr/SPARK-4586 and squashes the following commits:

415268e [Xiangrui Meng] remove inherit_doc from __init__
edbd6fe [Xiangrui Meng] move Identifiable to ml.util
44c2405 [Xiangrui Meng] Merge pull request #2 from davies/ml
dd1256b [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-4586
14ae7e2 [Davies Liu] fix docs
54ca7df [Davies Liu] fix tests
78638df [Davies Liu] Merge branch 'SPARK-4586' of github.com:mengxr/spark into ml
fc59a02 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-4586
1dca16a [Davies Liu] refactor
090b3a3 [Davies Liu] Merge branch 'master' of github.com:apache/spark into ml
0882513 [Xiangrui Meng] update doc style
a4f4dbf [Xiangrui Meng] add unit test for LR
7521d1c [Xiangrui Meng] add unit tests to HashingTF and Tokenizer
ba0ba1e [Xiangrui Meng] add unit tests for pipeline
0586c7b [Xiangrui Meng] add more comments to the example
5153cff [Xiangrui Meng] simplify java models
036ca04 [Xiangrui Meng] gen numFeatures
46fa147 [Xiangrui Meng] update mllib/pom.xml to include python files in the assembly
1dcc17e [Xiangrui Meng] update code gen and make param appear in the doc
f66ba0c [Xiangrui Meng] make params a property
d5efd34 [Xiangrui Meng] update doc conf and move embedded param map to instance attribute
f4d0fe6 [Xiangrui Meng] use LabeledDocument and Document in example
05e3e40 [Xiangrui Meng] update example
d3e8dbe [Xiangrui Meng] more docs optimize pipeline.fit impl
56de571 [Xiangrui Meng] fix style
d0c5bb8 [Xiangrui Meng] a working copy
bce72f4 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-4586
17ecfb9 [Xiangrui Meng] code gen for shared params
d9ea77c [Xiangrui Meng] update doc
c18dca1 [Xiangrui Meng] make the example working
dadd84e [Xiangrui Meng] add base classes and docs
a3015cf [Xiangrui Meng] add Estimator and Transformer
46eea43 [Xiangrui Meng] a pipeline in python
33b68e0 [Xiangrui Meng] a working LR

3 files changed, 440 insertions, 0 deletions

diff --git a/python/pyspark/ml/param/__init__.py b/python/pyspark/ml/param/__init__.py
new file mode 100644
index 0000000000..5566792cea
--- /dev/null
+++ b/python/pyspark/ml/param/__init__.py
@@ -0,0 +1,82 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+from abc import ABCMeta
+
+from pyspark.ml.util import Identifiable
+
+
+__all__ = ['Param', 'Params']
+
+
+class Param(object):
+    """
+    A param with self-contained documentation and optionally default value.
+    """
+
+    def __init__(self, parent, name, doc, defaultValue=None):
+        if not isinstance(parent, Identifiable):
+            raise ValueError("Parent must be identifiable but got type %s." % type(parent).__name__)
+        self.parent = parent
+        self.name = str(name)
+        self.doc = str(doc)
+        self.defaultValue = defaultValue
+
+    def __str__(self):
+        return str(self.parent) + "-" + self.name
+
+    def __repr__(self):
+        return "Param(parent=%r, name=%r, doc=%r, defaultValue=%r)" % \
+               (self.parent, self.name, self.doc, self.defaultValue)
+
+
+class Params(Identifiable):
+    """
+    Components that take parameters. This also provides an internal
+    param map to store parameter values attached to the instance.
+    """
+
+    __metaclass__ = ABCMeta
+
+    def __init__(self):
+        super(Params, self).__init__()
+        #: embedded param map
+        self.paramMap = {}
+
+    @property
+    def params(self):
+        """
+        Returns all params. The default implementation uses
+        :py:func:`dir` to get all attributes of type
+        :py:class:`Param`.
+        """
+        return filter(lambda attr: isinstance(attr, Param),
+                      [getattr(self, x) for x in dir(self) if x != "params"])
+
+    def _merge_params(self, params):
+        paramMap = self.paramMap.copy()
+        paramMap.update(params)
+        return paramMap
+
+    @staticmethod
+    def _dummy():
+        """
+        Returns a dummy Params instance used as a placeholder to generate docs.
+        """
+        dummy = Params()
+        dummy.uid = "undefined"
+        return dummy
diff --git a/python/pyspark/ml/param/_gen_shared_params.py b/python/pyspark/ml/param/_gen_shared_params.py
new file mode 100644
index 0000000000..5eb81106f1
--- /dev/null
+++ b/python/pyspark/ml/param/_gen_shared_params.py
@@ -0,0 +1,98 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+header = """#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#"""
+
+
+def _gen_param_code(name, doc, defaultValue):
+    """
+    Generates Python code for a shared param class.
+
+    :param name: param name
+    :param doc: param doc
+    :param defaultValue: string representation of the param
+    :return: code string
+    """
+    # TODO: How to correctly inherit instance attributes?
+    template = '''class Has$Name(Params):
+    """
+    Params with $name.
+    """
+
+    # a placeholder to make it appear in the generated doc
+    $name = Param(Params._dummy(), "$name", "$doc", $defaultValue)
+
+    def __init__(self):
+        super(Has$Name, self).__init__()
+        #: param for $doc
+        self.$name = Param(self, "$name", "$doc", $defaultValue)
+
+    def set$Name(self, value):
+        """
+        Sets the value of :py:attr:`$name`.
+        """
+        self.paramMap[self.$name] = value
+        return self
+
+    def get$Name(self):
+        """
+        Gets the value of $name or its default value.
+        """
+        if self.$name in self.paramMap:
+            return self.paramMap[self.$name]
+        else:
+            return self.$name.defaultValue'''
+
+    upperCamelName = name[0].upper() + name[1:]
+    return template \
+        .replace("$name", name) \
+        .replace("$Name", upperCamelName) \
+        .replace("$doc", doc) \
+        .replace("$defaultValue", defaultValue)
+
+if __name__ == "__main__":
+    print header
+    print "\n# DO NOT MODIFY. The code is generated by _gen_shared_params.py.\n"
+    print "from pyspark.ml.param import Param, Params\n\n"
+    shared = [
+        ("maxIter", "max number of iterations", "100"),
+        ("regParam", "regularization constant", "0.1"),
+        ("featuresCol", "features column name", "'features'"),
+        ("labelCol", "label column name", "'label'"),
+        ("predictionCol", "prediction column name", "'prediction'"),
+        ("inputCol", "input column name", "'input'"),
+        ("outputCol", "output column name", "'output'"),
+        ("numFeatures", "number of features", "1 << 18")]
+    code = []
+    for name, doc, defaultValue in shared:
+        code.append(_gen_param_code(name, doc, defaultValue))
+    print "\n\n\n".join(code)
diff --git a/python/pyspark/ml/param/shared.py b/python/pyspark/ml/param/shared.py
new file mode 100644
index 0000000000..586822f2de
--- /dev/null
+++ b/python/pyspark/ml/param/shared.py
@@ -0,0 +1,260 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License.  You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+# DO NOT MODIFY. The code is generated by _gen_shared_params.py.
+
+from pyspark.ml.param import Param, Params
+
+
+class HasMaxIter(Params):
+    """
+    Params with maxIter.
+    """
+
+    # a placeholder to make it appear in the generated doc
+    maxIter = Param(Params._dummy(), "maxIter", "max number of iterations", 100)
+
+    def __init__(self):
+        super(HasMaxIter, self).__init__()
+        #: param for max number of iterations
+        self.maxIter = Param(self, "maxIter", "max number of iterations", 100)
+
+    def setMaxIter(self, value):
+        """
+        Sets the value of :py:attr:`maxIter`.
+        """
+        self.paramMap[self.maxIter] = value
+        return self
+
+    def getMaxIter(self):
+        """
+        Gets the value of maxIter or its default value.
+        """
+        if self.maxIter in self.paramMap:
+            return self.paramMap[self.maxIter]
+        else:
+            return self.maxIter.defaultValue
+
+
+class HasRegParam(Params):
+    """
+    Params with regParam.
+    """
+
+    # a placeholder to make it appear in the generated doc
+    regParam = Param(Params._dummy(), "regParam", "regularization constant", 0.1)
+
+    def __init__(self):
+        super(HasRegParam, self).__init__()
+        #: param for regularization constant
+        self.regParam = Param(self, "regParam", "regularization constant", 0.1)
+
+    def setRegParam(self, value):
+        """
+        Sets the value of :py:attr:`regParam`.
+        """
+        self.paramMap[self.regParam] = value
+        return self
+
+    def getRegParam(self):
+        """
+        Gets the value of regParam or its default value.
+        """
+        if self.regParam in self.paramMap:
+            return self.paramMap[self.regParam]
+        else:
+            return self.regParam.defaultValue
+
+
+class HasFeaturesCol(Params):
+    """
+    Params with featuresCol.
+    """
+
+    # a placeholder to make it appear in the generated doc
+    featuresCol = Param(Params._dummy(), "featuresCol", "features column name", 'features')
+
+    def __init__(self):
+        super(HasFeaturesCol, self).__init__()
+        #: param for features column name
+        self.featuresCol = Param(self, "featuresCol", "features column name", 'features')
+
+    def setFeaturesCol(self, value):
+        """
+        Sets the value of :py:attr:`featuresCol`.
+        """
+        self.paramMap[self.featuresCol] = value
+        return self
+
+    def getFeaturesCol(self):
+        """
+        Gets the value of featuresCol or its default value.
+        """
+        if self.featuresCol in self.paramMap:
+            return self.paramMap[self.featuresCol]
+        else:
+            return self.featuresCol.defaultValue
+
+
+class HasLabelCol(Params):
+    """
+    Params with labelCol.
+    """
+
+    # a placeholder to make it appear in the generated doc
+    labelCol = Param(Params._dummy(), "labelCol", "label column name", 'label')
+
+    def __init__(self):
+        super(HasLabelCol, self).__init__()
+        #: param for label column name
+        self.labelCol = Param(self, "labelCol", "label column name", 'label')
+
+    def setLabelCol(self, value):
+        """
+        Sets the value of :py:attr:`labelCol`.
+        """
+        self.paramMap[self.labelCol] = value
+        return self
+
+    def getLabelCol(self):
+        """
+        Gets the value of labelCol or its default value.
+        """
+        if self.labelCol in self.paramMap:
+            return self.paramMap[self.labelCol]
+        else:
+            return self.labelCol.defaultValue
+
+
+class HasPredictionCol(Params):
+    """
+    Params with predictionCol.
+    """
+
+    # a placeholder to make it appear in the generated doc
+    predictionCol = Param(Params._dummy(), "predictionCol", "prediction column name", 'prediction')
+
+    def __init__(self):
+        super(HasPredictionCol, self).__init__()
+        #: param for prediction column name
+        self.predictionCol = Param(self, "predictionCol", "prediction column name", 'prediction')
+
+    def setPredictionCol(self, value):
+        """
+        Sets the value of :py:attr:`predictionCol`.
+        """
+        self.paramMap[self.predictionCol] = value
+        return self
+
+    def getPredictionCol(self):
+        """
+        Gets the value of predictionCol or its default value.
+        """
+        if self.predictionCol in self.paramMap:
+            return self.paramMap[self.predictionCol]
+        else:
+            return self.predictionCol.defaultValue
+
+
+class HasInputCol(Params):
+    """
+    Params with inputCol.
+    """
+
+    # a placeholder to make it appear in the generated doc
+    inputCol = Param(Params._dummy(), "inputCol", "input column name", 'input')
+
+    def __init__(self):
+        super(HasInputCol, self).__init__()
+        #: param for input column name
+        self.inputCol = Param(self, "inputCol", "input column name", 'input')
+
+    def setInputCol(self, value):
+        """
+        Sets the value of :py:attr:`inputCol`.
+        """
+        self.paramMap[self.inputCol] = value
+        return self
+
+    def getInputCol(self):
+        """
+        Gets the value of inputCol or its default value.
+        """
+        if self.inputCol in self.paramMap:
+            return self.paramMap[self.inputCol]
+        else:
+            return self.inputCol.defaultValue
+
+
+class HasOutputCol(Params):
+    """
+    Params with outputCol.
+    """
+
+    # a placeholder to make it appear in the generated doc
+    outputCol = Param(Params._dummy(), "outputCol", "output column name", 'output')
+
+    def __init__(self):
+        super(HasOutputCol, self).__init__()
+        #: param for output column name
+        self.outputCol = Param(self, "outputCol", "output column name", 'output')
+
+    def setOutputCol(self, value):
+        """
+        Sets the value of :py:attr:`outputCol`.
+        """
+        self.paramMap[self.outputCol] = value
+        return self
+
+    def getOutputCol(self):
+        """
+        Gets the value of outputCol or its default value.
+        """
+        if self.outputCol in self.paramMap:
+            return self.paramMap[self.outputCol]
+        else:
+            return self.outputCol.defaultValue
+
+
+class HasNumFeatures(Params):
+    """
+    Params with numFeatures.
+    """
+
+    # a placeholder to make it appear in the generated doc
+    numFeatures = Param(Params._dummy(), "numFeatures", "number of features", 1 << 18)
+
+    def __init__(self):
+        super(HasNumFeatures, self).__init__()
+        #: param for number of features
+        self.numFeatures = Param(self, "numFeatures", "number of features", 1 << 18)
+
+    def setNumFeatures(self, value):
+        """
+        Sets the value of :py:attr:`numFeatures`.
+        """
+        self.paramMap[self.numFeatures] = value
+        return self
+
+    def getNumFeatures(self):
+        """
+        Gets the value of numFeatures or its default value.
+        """
+        if self.numFeatures in self.paramMap:
+            return self.paramMap[self.numFeatures]
+        else:
+            return self.numFeatures.defaultValue