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Github user jkbradley commented on the pull request: https://github.com/apache/spark/pull/8102#issuecomment-139083436 LGTM. Merging with master. Thank you! --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user jkbradley commented on the pull request: https://github.com/apache/spark/pull/8102#issuecomment-132345003 One more comment: need to add VectorSlicer to list ```__all__``` at top of file --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user jkbradley commented on a diff in the pull request: https://github.com/apache/spark/pull/8102#discussion_r37350810 --- Diff: python/pyspark/ml/feature.py --- @@ -950,6 +950,92 @@ class VectorIndexerModel(JavaModel): @inherit_doc +class VectorSlicer(JavaTransformer, HasInputCol, HasOutputCol): +""" +.. note:: Experimental + +This class takes a feature vector and outputs a new feature vector with a subarray +of the original features. + +The subset of features can be specified with either indices (`setIndices()`) +or names (`setNames()`). At least one feature must be selected. Duplicate features +are not allowed, so there can be no overlap between selected indices and names. + +The output vector will order features with the selected indices first (in the order given), +followed by the selected names (in the order given). + +>>> from pyspark.mllib.linalg import Vectors +>>> df = sqlContext.createDataFrame([ +... (Vectors.dense([-2.0, 2.3, 0.0, 0.0, 1.0]),), +... (Vectors.dense([0.0, 0.0, 0.0, 0.0, 0.0]),), +... (Vectors.dense([0.6, -1.1, -3.0, 4.5, 3.3]),)], ["features"]) +>>> vs = VectorSlicer(inputCol="features", outputCol="expected", indices=[1, 4]) +>>> vs.transform(df).head().expected +DenseVector([2.3, 1.0]) +""" + +# a placeholder to make it appear in the generated doc +indices = Param(Params._dummy(), "indices", "An array of indices to select features from " + +"a vector column. There can be no overlap with `names`.") +names = Param(Params._dummy(), "names", "An array of feature names to select features from " + + "a vector column. These names must be specified by ML " + + "`org.apache.spark.ml.attribute.Attribute`s. There can be no overlap with " + + "`indices`.") + +@keyword_only +def __init__(self, inputCol=None, outputCol=None, indices=[], names=[]): --- End diff -- In Python, we should avoid using mutable values ```[]``` as defaults. Let's use None. The Scala API should take care of the defaults. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user jkbradley commented on a diff in the pull request: https://github.com/apache/spark/pull/8102#discussion_r37350798 --- Diff: python/pyspark/ml/feature.py --- @@ -950,6 +950,92 @@ class VectorIndexerModel(JavaModel): @inherit_doc +class VectorSlicer(JavaTransformer, HasInputCol, HasOutputCol): +""" +.. note:: Experimental + +This class takes a feature vector and outputs a new feature vector with a subarray +of the original features. + +The subset of features can be specified with either indices (`setIndices()`) +or names (`setNames()`). At least one feature must be selected. Duplicate features +are not allowed, so there can be no overlap between selected indices and names. + +The output vector will order features with the selected indices first (in the order given), +followed by the selected names (in the order given). + +>>> from pyspark.mllib.linalg import Vectors +>>> df = sqlContext.createDataFrame([ +... (Vectors.dense([-2.0, 2.3, 0.0, 0.0, 1.0]),), +... (Vectors.dense([0.0, 0.0, 0.0, 0.0, 0.0]),), +... (Vectors.dense([0.6, -1.1, -3.0, 4.5, 3.3]),)], ["features"]) +>>> vs = VectorSlicer(inputCol="features", outputCol="expected", indices=[1, 4]) --- End diff -- Rename "expected" to "sliced" since this is an example --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/8102#discussion_r37350812
--- Diff: python/pyspark/ml/feature.py ---
@@ -950,6 +950,92 @@ class VectorIndexerModel(JavaModel):
@inherit_doc
+class VectorSlicer(JavaTransformer, HasInputCol, HasOutputCol):
+"""
+.. note:: Experimental
+
+This class takes a feature vector and outputs a new feature vector
with a subarray
+of the original features.
+
+The subset of features can be specified with either indices
(`setIndices()`)
+or names (`setNames()`). At least one feature must be selected.
Duplicate features
+are not allowed, so there can be no overlap between selected indices
and names.
+
+The output vector will order features with the selected indices first
(in the order given),
+followed by the selected names (in the order given).
+
+>>> from pyspark.mllib.linalg import Vectors
+>>> df = sqlContext.createDataFrame([
+... (Vectors.dense([-2.0, 2.3, 0.0, 0.0, 1.0]),),
+... (Vectors.dense([0.0, 0.0, 0.0, 0.0, 0.0]),),
+... (Vectors.dense([0.6, -1.1, -3.0, 4.5, 3.3]),)], ["features"])
+>>> vs = VectorSlicer(inputCol="features", outputCol="expected",
indices=[1, 4])
+>>> vs.transform(df).head().expected
+DenseVector([2.3, 1.0])
+"""
+
+# a placeholder to make it appear in the generated doc
+indices = Param(Params._dummy(), "indices", "An array of indices to
select features from " +
+"a vector column. There can be no overlap with
`names`.")
+names = Param(Params._dummy(), "names", "An array of feature names to
select features from " +
+ "a vector column. These names must be specified by ML " +
+ "`org.apache.spark.ml.attribute.Attribute`s. There can
be no overlap with " +
+ "`indices`.")
+
+@keyword_only
+def __init__(self, inputCol=None, outputCol=None, indices=[],
names=[]):
+"""
+__init__(self, inputCol=None, outputCol=None, indices=[], names=[])
+"""
+super(VectorSlicer, self).__init__()
+self._java_obj =
self._new_java_obj("org.apache.spark.ml.feature.VectorSlicer", self.uid)
+self.indices = Param(self, "indices", "An array of indices to
select features from " +
+ "a vector column. There can be no overlap
with `names`.")
+self.names = Param(self, "names", "An array of feature names to
select features from " +
+ "a vector column. These names must be specified
by ML " +
+ "`org.apache.spark.ml.attribute.Attribute`s.
There can be no overlap " +
+ "with `indices`.")
+self._setDefault(indices=[], names=[])
--- End diff --
so no defaults here
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[GitHub] spark pull request: [SPARK-9772] [PySpark] [ML] Add Python API for...
Github user jkbradley commented on a diff in the pull request: https://github.com/apache/spark/pull/8102#discussion_r37350805 --- Diff: python/pyspark/ml/feature.py --- @@ -950,6 +950,92 @@ class VectorIndexerModel(JavaModel): @inherit_doc +class VectorSlicer(JavaTransformer, HasInputCol, HasOutputCol): +""" +.. note:: Experimental + +This class takes a feature vector and outputs a new feature vector with a subarray +of the original features. + +The subset of features can be specified with either indices (`setIndices()`) +or names (`setNames()`). At least one feature must be selected. Duplicate features +are not allowed, so there can be no overlap between selected indices and names. + +The output vector will order features with the selected indices first (in the order given), +followed by the selected names (in the order given). + +>>> from pyspark.mllib.linalg import Vectors +>>> df = sqlContext.createDataFrame([ +... (Vectors.dense([-2.0, 2.3, 0.0, 0.0, 1.0]),), +... (Vectors.dense([0.0, 0.0, 0.0, 0.0, 0.0]),), +... (Vectors.dense([0.6, -1.1, -3.0, 4.5, 3.3]),)], ["features"]) +>>> vs = VectorSlicer(inputCol="features", outputCol="expected", indices=[1, 4]) +>>> vs.transform(df).head().expected +DenseVector([2.3, 1.0]) +""" + +# a placeholder to make it appear in the generated doc +indices = Param(Params._dummy(), "indices", "An array of indices to select features from " + +"a vector column. There can be no overlap with `names`.") +names = Param(Params._dummy(), "names", "An array of feature names to select features from " + + "a vector column. These names must be specified by ML " + + "`org.apache.spark.ml.attribute.Attribute`s. There can be no overlap with " + --- End diff -- No need for backtick within strings; the backtick is only for formatting generated API docs. (here and elsewhere) --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-9772] [PySpark] [ML] Add Python API for...
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[GitHub] spark pull request: [SPARK-9772] [PySpark] [ML] Add Python API for...
Github user SparkQA commented on the pull request: https://github.com/apache/spark/pull/8102#issuecomment-130872159 [Test build #40826 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/40826/console) for PR 8102 at commit [`54bffab`](https://github.com/apache/spark/commit/54bffab42600aa184eb01134410f266199d19a97). * This patch **passes all tests**. * This patch merges cleanly. * This patch adds the following public classes _(experimental)_: * `class VectorSlicer(JavaTransformer, HasInputCol, HasOutputCol):` --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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