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author | Yu ISHIKAWA <yuu.ishikawa@gmail.com> | 2015-09-17 08:51:19 -0700 |
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committer | Xiangrui Meng <meng@databricks.com> | 2015-09-17 08:51:19 -0700 |
commit | 268088b899e6e165e746aed87840d47bfaf50c43 (patch) | |
tree | d17b1741cda933f2034fa2c6158e8569e28a5446 | |
parent | c74d38fd8faf8cba981cf934341d24b9a3167025 (diff) | |
download | spark-268088b899e6e165e746aed87840d47bfaf50c43.tar.gz spark-268088b899e6e165e746aed87840d47bfaf50c43.tar.bz2 spark-268088b899e6e165e746aed87840d47bfaf50c43.zip |
[SPARK-10282] [ML] [PYSPARK] [DOCS] Add @since annotation to pyspark.ml.recommendation
Author: Yu ISHIKAWA <yuu.ishikawa@gmail.com>
Closes #8692 from yu-iskw/SPARK-10282.
-rw-r--r-- | python/pyspark/ml/recommendation.py | 28 |
1 files changed, 28 insertions, 0 deletions
diff --git a/python/pyspark/ml/recommendation.py b/python/pyspark/ml/recommendation.py index b06099ac0a..ec5748a1cf 100644 --- a/python/pyspark/ml/recommendation.py +++ b/python/pyspark/ml/recommendation.py @@ -15,6 +15,7 @@ # limitations under the License. # +from pyspark import since from pyspark.ml.util import keyword_only from pyspark.ml.wrapper import JavaEstimator, JavaModel from pyspark.ml.param.shared import * @@ -80,6 +81,8 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha Row(user=1, item=0, prediction=3.19...) >>> predictions[2] Row(user=2, item=0, prediction=-1.15...) + + .. versionadded:: 1.4.0 """ # a placeholder to make it appear in the generated doc @@ -122,6 +125,7 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha self.setParams(**kwargs) @keyword_only + @since("1.4.0") def setParams(self, rank=10, maxIter=10, regParam=0.1, numUserBlocks=10, numItemBlocks=10, implicitPrefs=False, alpha=1.0, userCol="user", itemCol="item", seed=None, ratingCol="rating", nonnegative=False, checkpointInterval=10): @@ -137,6 +141,7 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha def _create_model(self, java_model): return ALSModel(java_model) + @since("1.4.0") def setRank(self, value): """ Sets the value of :py:attr:`rank`. @@ -144,12 +149,14 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha self._paramMap[self.rank] = value return self + @since("1.4.0") def getRank(self): """ Gets the value of rank or its default value. """ return self.getOrDefault(self.rank) + @since("1.4.0") def setNumUserBlocks(self, value): """ Sets the value of :py:attr:`numUserBlocks`. @@ -157,12 +164,14 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha self._paramMap[self.numUserBlocks] = value return self + @since("1.4.0") def getNumUserBlocks(self): """ Gets the value of numUserBlocks or its default value. """ return self.getOrDefault(self.numUserBlocks) + @since("1.4.0") def setNumItemBlocks(self, value): """ Sets the value of :py:attr:`numItemBlocks`. @@ -170,12 +179,14 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha self._paramMap[self.numItemBlocks] = value return self + @since("1.4.0") def getNumItemBlocks(self): """ Gets the value of numItemBlocks or its default value. """ return self.getOrDefault(self.numItemBlocks) + @since("1.4.0") def setNumBlocks(self, value): """ Sets both :py:attr:`numUserBlocks` and :py:attr:`numItemBlocks` to the specific value. @@ -183,6 +194,7 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha self._paramMap[self.numUserBlocks] = value self._paramMap[self.numItemBlocks] = value + @since("1.4.0") def setImplicitPrefs(self, value): """ Sets the value of :py:attr:`implicitPrefs`. @@ -190,12 +202,14 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha self._paramMap[self.implicitPrefs] = value return self + @since("1.4.0") def getImplicitPrefs(self): """ Gets the value of implicitPrefs or its default value. """ return self.getOrDefault(self.implicitPrefs) + @since("1.4.0") def setAlpha(self, value): """ Sets the value of :py:attr:`alpha`. @@ -203,12 +217,14 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha self._paramMap[self.alpha] = value return self + @since("1.4.0") def getAlpha(self): """ Gets the value of alpha or its default value. """ return self.getOrDefault(self.alpha) + @since("1.4.0") def setUserCol(self, value): """ Sets the value of :py:attr:`userCol`. @@ -216,12 +232,14 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha self._paramMap[self.userCol] = value return self + @since("1.4.0") def getUserCol(self): """ Gets the value of userCol or its default value. """ return self.getOrDefault(self.userCol) + @since("1.4.0") def setItemCol(self, value): """ Sets the value of :py:attr:`itemCol`. @@ -229,12 +247,14 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha self._paramMap[self.itemCol] = value return self + @since("1.4.0") def getItemCol(self): """ Gets the value of itemCol or its default value. """ return self.getOrDefault(self.itemCol) + @since("1.4.0") def setRatingCol(self, value): """ Sets the value of :py:attr:`ratingCol`. @@ -242,12 +262,14 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha self._paramMap[self.ratingCol] = value return self + @since("1.4.0") def getRatingCol(self): """ Gets the value of ratingCol or its default value. """ return self.getOrDefault(self.ratingCol) + @since("1.4.0") def setNonnegative(self, value): """ Sets the value of :py:attr:`nonnegative`. @@ -255,6 +277,7 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha self._paramMap[self.nonnegative] = value return self + @since("1.4.0") def getNonnegative(self): """ Gets the value of nonnegative or its default value. @@ -265,14 +288,18 @@ class ALS(JavaEstimator, HasCheckpointInterval, HasMaxIter, HasPredictionCol, Ha class ALSModel(JavaModel): """ Model fitted by ALS. + + .. versionadded:: 1.4.0 """ @property + @since("1.4.0") def rank(self): """rank of the matrix factorization model""" return self._call_java("rank") @property + @since("1.4.0") def userFactors(self): """ a DataFrame that stores user factors in two columns: `id` and @@ -281,6 +308,7 @@ class ALSModel(JavaModel): return self._call_java("userFactors") @property + @since("1.4.0") def itemFactors(self): """ a DataFrame that stores item factors in two columns: `id` and |