diff options
Diffstat (limited to 'python/pyspark')
-rw-r--r-- | python/pyspark/ml/feature.py | 28 | ||||
-rw-r--r-- | python/pyspark/ml/tests.py | 5 | ||||
-rw-r--r-- | python/pyspark/mllib/feature.py | 11 | ||||
-rw-r--r-- | python/pyspark/mllib/tests.py | 4 |
4 files changed, 41 insertions, 7 deletions
diff --git a/python/pyspark/ml/feature.py b/python/pyspark/ml/feature.py index 776906eaab..49a78ede37 100644 --- a/python/pyspark/ml/feature.py +++ b/python/pyspark/ml/feature.py @@ -2219,28 +2219,31 @@ class Word2Vec(JavaEstimator, HasStepSize, HasMaxIter, HasSeed, HasInputCol, Has minCount = Param(Params._dummy(), "minCount", "the minimum number of times a token must appear to be included in the " + "word2vec model's vocabulary", typeConverter=TypeConverters.toInt) + windowSize = Param(Params._dummy(), "windowSize", + "the window size (context words from [-window, window]). Default value is 5", + typeConverter=TypeConverters.toInt) @keyword_only def __init__(self, vectorSize=100, minCount=5, numPartitions=1, stepSize=0.025, maxIter=1, - seed=None, inputCol=None, outputCol=None): + seed=None, inputCol=None, outputCol=None, windowSize=5): """ __init__(self, vectorSize=100, minCount=5, numPartitions=1, stepSize=0.025, maxIter=1, \ - seed=None, inputCol=None, outputCol=None) + seed=None, inputCol=None, outputCol=None, windowSize=5) """ super(Word2Vec, self).__init__() self._java_obj = self._new_java_obj("org.apache.spark.ml.feature.Word2Vec", self.uid) self._setDefault(vectorSize=100, minCount=5, numPartitions=1, stepSize=0.025, maxIter=1, - seed=None) + seed=None, windowSize=5) kwargs = self.__init__._input_kwargs self.setParams(**kwargs) @keyword_only @since("1.4.0") def setParams(self, vectorSize=100, minCount=5, numPartitions=1, stepSize=0.025, maxIter=1, - seed=None, inputCol=None, outputCol=None): + seed=None, inputCol=None, outputCol=None, windowSize=5): """ setParams(self, minCount=5, numPartitions=1, stepSize=0.025, maxIter=1, seed=None, \ - inputCol=None, outputCol=None) + inputCol=None, outputCol=None, windowSize=5) Sets params for this Word2Vec. """ kwargs = self.setParams._input_kwargs @@ -2291,6 +2294,21 @@ class Word2Vec(JavaEstimator, HasStepSize, HasMaxIter, HasSeed, HasInputCol, Has """ return self.getOrDefault(self.minCount) + @since("2.0.0") + def setWindowSize(self, value): + """ + Sets the value of :py:attr:`windowSize`. + """ + self._set(windowSize=value) + return self + + @since("2.0.0") + def getWindowSize(self): + """ + Gets the value of windowSize or its default value. + """ + return self.getOrDefault(self.windowSize) + def _create_model(self, java_model): return Word2VecModel(java_model) diff --git a/python/pyspark/ml/tests.py b/python/pyspark/ml/tests.py index 9d6ff47b54..f1bca6ebe0 100644 --- a/python/pyspark/ml/tests.py +++ b/python/pyspark/ml/tests.py @@ -341,6 +341,11 @@ class ParamTests(PySparkTestCase): params = param_store.params # should not invoke the property 'test_property' self.assertEqual(len(params), 1) + def test_word2vec_param(self): + model = Word2Vec().setWindowSize(6) + # Check windowSize is set properly + self.assertEqual(model.getWindowSize(), 6) + class FeatureTests(PySparkTestCase): diff --git a/python/pyspark/mllib/feature.py b/python/pyspark/mllib/feature.py index b3dd2f63a5..90559f6cfb 100644 --- a/python/pyspark/mllib/feature.py +++ b/python/pyspark/mllib/feature.py @@ -617,6 +617,7 @@ class Word2Vec(object): self.numIterations = 1 self.seed = random.randint(0, sys.maxsize) self.minCount = 5 + self.windowSize = 5 @since('1.2.0') def setVectorSize(self, vectorSize): @@ -669,6 +670,14 @@ class Word2Vec(object): self.minCount = minCount return self + @since('2.0.0') + def setWindowSize(self, windowSize): + """ + Sets window size (default: 5). + """ + self.windowSize = windowSize + return self + @since('1.2.0') def fit(self, data): """ @@ -682,7 +691,7 @@ class Word2Vec(object): jmodel = callMLlibFunc("trainWord2VecModel", data, int(self.vectorSize), float(self.learningRate), int(self.numPartitions), int(self.numIterations), int(self.seed), - int(self.minCount)) + int(self.minCount), int(self.windowSize)) return Word2VecModel(jmodel) diff --git a/python/pyspark/mllib/tests.py b/python/pyspark/mllib/tests.py index ac55fbf798..f272da56d1 100644 --- a/python/pyspark/mllib/tests.py +++ b/python/pyspark/mllib/tests.py @@ -1027,13 +1027,15 @@ class Word2VecTests(MLlibTestCase): .setNumPartitions(2) \ .setNumIterations(10) \ .setSeed(1024) \ - .setMinCount(3) + .setMinCount(3) \ + .setWindowSize(6) self.assertEqual(model.vectorSize, 2) self.assertTrue(model.learningRate < 0.02) self.assertEqual(model.numPartitions, 2) self.assertEqual(model.numIterations, 10) self.assertEqual(model.seed, 1024) self.assertEqual(model.minCount, 3) + self.assertEqual(model.windowSize, 6) def test_word2vec_get_vectors(self): data = [ |