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author | Imran Rashid <irashid@cloudera.com> | 2015-11-06 20:06:24 +0000 |
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committer | Sean Owen <sowen@cloudera.com> | 2015-11-06 20:06:24 +0000 |
commit | 49f1a820372d1cba41f3f00d07eb5728f2ed6705 (patch) | |
tree | 535797cc3662bfd7d8247b2d01f6fd00b2e1b2a9 /python/pyspark/ml | |
parent | 62bb290773c9f9fa53cbe6d4eedc6e153761a763 (diff) | |
download | spark-49f1a820372d1cba41f3f00d07eb5728f2ed6705.tar.gz spark-49f1a820372d1cba41f3f00d07eb5728f2ed6705.tar.bz2 spark-49f1a820372d1cba41f3f00d07eb5728f2ed6705.zip |
[SPARK-10116][CORE] XORShiftRandom.hashSeed is random in high bits
https://issues.apache.org/jira/browse/SPARK-10116
This is really trivial, just happened to notice it -- if `XORShiftRandom.hashSeed` is really supposed to have random bits throughout (as the comment implies), it needs to do something for the conversion to `long`.
mengxr mkolod
Author: Imran Rashid <irashid@cloudera.com>
Closes #8314 from squito/SPARK-10116.
Diffstat (limited to 'python/pyspark/ml')
-rw-r--r-- | python/pyspark/ml/feature.py | 20 | ||||
-rw-r--r-- | python/pyspark/ml/recommendation.py | 6 |
2 files changed, 13 insertions, 13 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 """ |