diff options
Diffstat (limited to 'python')
| -rw-r--r-- | python/pyspark/ml/feature.py | 20 | ||||
| -rw-r--r-- | python/pyspark/ml/recommendation.py | 6 | ||||
| -rw-r--r-- | python/pyspark/mllib/recommendation.py | 4 | ||||
| -rw-r--r-- | python/pyspark/sql/dataframe.py | 6 |
4 files changed, 18 insertions, 18 deletions
diff --git a/python/pyspark/ml/feature.py b/python/pyspark/ml/feature.py index c7b6dd926c..b02d41b52a 100644 --- a/python/pyspark/ml/feature.py +++ b/python/pyspark/ml/feature.py @@ -1788,21 +1788,21 @@ class Word2Vec(JavaEstimator, HasStepSize, HasMaxIter, HasSeed, HasInputCol, Has +----+--------------------+ |word| vector| +----+--------------------+ - | a|[-0.3511952459812...| - | b|[0.29077222943305...| - | c|[0.02315592765808...| + | a|[0.09461779892444...| + | b|[1.15474212169647...| + | c|[-0.3794820010662...| +----+--------------------+ ... >>> model.findSynonyms("a", 2).show() - +----+-------------------+ - |word| similarity| - +----+-------------------+ - | b|0.29255685145799626| - | c|-0.5414068302988307| - +----+-------------------+ + +----+--------------------+ + |word| similarity| + +----+--------------------+ + | b| 0.16782984556103436| + | c|-0.46761559092107646| + +----+--------------------+ ... >>> model.transform(doc).head().model - DenseVector([-0.0422, -0.5138, -0.2546, 0.6885, 0.276]) + DenseVector([0.5524, -0.4995, -0.3599, 0.0241, 0.3461]) .. versionadded:: 1.4.0 """ diff --git a/python/pyspark/ml/recommendation.py b/python/pyspark/ml/recommendation.py index ec5748a1cf..b44c66f73c 100644 --- a/python/pyspark/ml/recommendation.py +++ b/python/pyspark/ml/recommendation.py @@ -76,11 +76,11 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha >>> test = sqlContext.createDataFrame([(0, 2), (1, 0), (2, 0)], ["user", "item"]) >>> predictions = sorted(model.transform(test).collect(), key=lambda r: r[0]) >>> predictions[0] - Row(user=0, item=2, prediction=0.39...) + Row(user=0, item=2, prediction=-0.13807615637779236) >>> predictions[1] - Row(user=1, item=0, prediction=3.19...) + Row(user=1, item=0, prediction=2.6258413791656494) >>> predictions[2] - Row(user=2, item=0, prediction=-1.15...) + Row(user=2, item=0, prediction=-1.5018409490585327) .. versionadded:: 1.4.0 """ diff --git a/python/pyspark/mllib/recommendation.py b/python/pyspark/mllib/recommendation.py index b9442b0d16..93e47a797f 100644 --- a/python/pyspark/mllib/recommendation.py +++ b/python/pyspark/mllib/recommendation.py @@ -101,12 +101,12 @@ class MatrixFactorizationModel(JavaModelWrapper, JavaSaveable, JavaLoader): >>> model = ALS.train(ratings, 1, nonnegative=True, seed=10) >>> model.predict(2, 2) - 3.8... + 3.73... >>> df = sqlContext.createDataFrame([Rating(1, 1, 1.0), Rating(1, 2, 2.0), Rating(2, 1, 2.0)]) >>> model = ALS.train(df, 1, nonnegative=True, seed=10) >>> model.predict(2, 2) - 3.8... + 3.73... >>> model = ALS.trainImplicit(ratings, 1, nonnegative=True, seed=10) >>> model.predict(2, 2) diff --git a/python/pyspark/sql/dataframe.py b/python/pyspark/sql/dataframe.py index 3baff81477..765a4511b6 100644 --- a/python/pyspark/sql/dataframe.py +++ b/python/pyspark/sql/dataframe.py @@ -436,7 +436,7 @@ class DataFrame(object): """Returns a sampled subset of this :class:`DataFrame`. >>> df.sample(False, 0.5, 42).count() - 1 + 2 """ assert fraction >= 0.0, "Negative fraction value: %s" % fraction seed = seed if seed is not None else random.randint(0, sys.maxsize) @@ -463,8 +463,8 @@ class DataFrame(object): +---+-----+ |key|count| +---+-----+ - | 0| 3| - | 1| 8| + | 0| 5| + | 1| 9| +---+-----+ """ |