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https://issues.apache.org/jira/browse/SPARK-9663?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Yanbo Liang updated SPARK-9663:
-------------------------------
Description:
This umbrella is for a list of Python API coverage issues which we should fix
for the 1.6 release cycle. This list is to be generated from issues found in
[SPARK-9662] and from remaining issues from 1.4: [SPARK-7536].
Here we check and compare the Python and Scala API of MLlib/ML,
add missing classes/methods/parameters for PySpark.
* Missing classes for PySpark:
** feature
*** CountVectorizerModel
*** DCT
*** ElementwiseProduct
*** MinMaxScaler
*** StopWordsRemover
*** VectorSlicer
** classification
*** OneVsRest
*** MultilayerPerceptronClassifier
** regression
*** IsotonicRegression
* Missing User Guide documents for PySpark
** MLlib
*** Isotonic regression
*** LDA
*** Streaming k-means
*** PCA
*** SVD
*** FP-growth
** For ML
*** feature
**** CountVectorizerModel
**** DCT
**** MinMaxScaler
**** StopWordsRemover
**** VectorSlicer
**** ElementwiseProduct
was:
This umbrella is for a list of Python API coverage issues which we should fix
for the 1.6 release cycle. This list is to be generated from issues found in
[SPARK-9662] and from remaining issues from 1.4: [SPARK-7536].
Here we check and compare the Python and Scala API of MLlib/ML,
add missing classes/methods/parameters for PySpark.
* Missing classes for PySpark:
** feature
*** CountVectorizerModel
*** DCT
*** ElementwiseProduct
*** MinMaxScaler
*** StopWordsRemover
*** VectorSlicer
** classification
*** OneVsRest
*** MultilayerPerceptronClassifier
** regression
*** IsotonicRegression
> ML Python API coverage issues found during 1.5 QA
> -------------------------------------------------
>
> Key: SPARK-9663
> URL: https://issues.apache.org/jira/browse/SPARK-9663
> Project: Spark
> Issue Type: Umbrella
> Components: ML, MLlib, PySpark
> Reporter: Joseph K. Bradley
>
> This umbrella is for a list of Python API coverage issues which we should fix
> for the 1.6 release cycle. This list is to be generated from issues found in
> [SPARK-9662] and from remaining issues from 1.4: [SPARK-7536].
> Here we check and compare the Python and Scala API of MLlib/ML,
> add missing classes/methods/parameters for PySpark.
> * Missing classes for PySpark:
> ** feature
> *** CountVectorizerModel
> *** DCT
> *** ElementwiseProduct
> *** MinMaxScaler
> *** StopWordsRemover
> *** VectorSlicer
> ** classification
> *** OneVsRest
> *** MultilayerPerceptronClassifier
> ** regression
> *** IsotonicRegression
> * Missing User Guide documents for PySpark
> ** MLlib
> *** Isotonic regression
> *** LDA
> *** Streaming k-means
> *** PCA
> *** SVD
> *** FP-growth
> ** For ML
> *** feature
> **** CountVectorizerModel
> **** DCT
> **** MinMaxScaler
> **** StopWordsRemover
> **** VectorSlicer
> **** ElementwiseProduct
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