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diff --git a/python/pyspark/ml/base.py b/python/pyspark/ml/base.py
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+#
+# 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, abstractmethod
+
+from pyspark import since
+from pyspark.ml.param import Params
+from pyspark.mllib.common import inherit_doc
+
+
+@inherit_doc
+class Estimator(Params):
+    """
+    Abstract class for estimators that fit models to data.
+
+    .. versionadded:: 1.3.0
+    """
+
+    __metaclass__ = ABCMeta
+
+    @abstractmethod
+    def _fit(self, dataset):
+        """
+        Fits a model to the input dataset. This is called by the default implementation of fit.
+
+        :param dataset: input dataset, which is an instance of :py:class:`pyspark.sql.DataFrame`
+        :returns: fitted model
+        """
+        raise NotImplementedError()
+
+    @since("1.3.0")
+    def fit(self, dataset, params=None):
+        """
+        Fits a model to the input dataset with optional parameters.
+
+        :param dataset: input dataset, which is an instance of :py:class:`pyspark.sql.DataFrame`
+        :param params: an optional param map that overrides embedded params. If a list/tuple of
+                       param maps is given, this calls fit on each param map and returns a list of
+                       models.
+        :returns: fitted model(s)
+        """
+        if params is None:
+            params = dict()
+        if isinstance(params, (list, tuple)):
+            return [self.fit(dataset, paramMap) for paramMap in params]
+        elif isinstance(params, dict):
+            if params:
+                return self.copy(params)._fit(dataset)
+            else:
+                return self._fit(dataset)
+        else:
+            raise ValueError("Params must be either a param map or a list/tuple of param maps, "
+                             "but got %s." % type(params))
+
+
+@inherit_doc
+class Transformer(Params):
+    """
+    Abstract class for transformers that transform one dataset into another.
+
+    .. versionadded:: 1.3.0
+    """
+
+    __metaclass__ = ABCMeta
+
+    @abstractmethod
+    def _transform(self, dataset):
+        """
+        Transforms the input dataset.
+
+        :param dataset: input dataset, which is an instance of :py:class:`pyspark.sql.DataFrame`
+        :returns: transformed dataset
+        """
+        raise NotImplementedError()
+
+    @since("1.3.0")
+    def transform(self, dataset, params=None):
+        """
+        Transforms the input dataset with optional parameters.
+
+        :param dataset: input dataset, which is an instance of :py:class:`pyspark.sql.DataFrame`
+        :param params: an optional param map that overrides embedded params.
+        :returns: transformed dataset
+        """
+        if params is None:
+            params = dict()
+        if isinstance(params, dict):
+            if params:
+                return self.copy(params)._transform(dataset)
+            else:
+                return self._transform(dataset)
+        else:
+            raise ValueError("Params must be a param map but got %s." % type(params))
+
+
+@inherit_doc
+class Model(Transformer):
+    """
+    Abstract class for models that are fitted by estimators.
+
+    .. versionadded:: 1.4.0
+    """
+
+    __metaclass__ = ABCMeta