diff options
Diffstat (limited to 'python/pyspark/ml/base.py')
-rw-r--r-- | python/pyspark/ml/base.py | 118 |
1 files changed, 118 insertions, 0 deletions
diff --git a/python/pyspark/ml/base.py b/python/pyspark/ml/base.py new file mode 100644 index 0000000000..a7a58e17a4 --- /dev/null +++ b/python/pyspark/ml/base.py @@ -0,0 +1,118 @@ +# +# 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 |