holdenk created SPARK-16814:
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Summary: Fix deprecated use of ParquetWriter in Parquet test suites
Key: SPARK-16814
URL: https://issues.apache.org/jira/browse/SPARK-16814
Project: Spark
Issue Type:
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holdenk commented on SPARK-16779:
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I've gone ahead and done a more full-scope version - l
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holdenk commented on SPARK-16776:
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Is this one you wanted to take on as well?
> Fix Kafk
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holdenk commented on SPARK-16777:
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Go for it :) Please CC me on the PR so I can do a code
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holdenk commented on SPARK-16777:
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That's a good point, thanks for the comment/note :) I
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holdenk commented on SPARK-16788:
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cc [~davies] [~ckadner] :)
> Investigate JSR-310 & sc
holdenk created SPARK-16788:
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Summary: Investigate JSR-310 & scala-time alternatives to our own
datetime utils
Key: SPARK-16788
URL: https://issues.apache.org/jira/browse/SPARK-16788
Project: Spark
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holdenk edited comment on SPARK-16774 at 7/28/16 11:38 PM:
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Whi
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holdenk updated SPARK-16774:
Description: The TimeStamp constructor we use inside of DateTime utils has
been deprecated since JDK 1.1 -
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holdenk updated SPARK-16774:
Description: The TimeStamp constructor we use inside of DateTime utils has
been deprecated since JDK 1.1 -
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holdenk updated SPARK-16774:
Summary: Fix use of deprecated TimeStamp constructor (also providing
incorrect results) (was: Fix use of d
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holdenk commented on SPARK-16774:
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While diving into this (relatedly I hate timezones) -
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holdenk edited comment on SPARK-16779 at 7/28/16 6:36 PM:
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I'm s
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holdenk commented on SPARK-16779:
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I'm sort of on the fence with fixing as well - but we
holdenk created SPARK-16779:
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Summary: Fix unnecessary use of postfix operations
Key: SPARK-16779
URL: https://issues.apache.org/jira/browse/SPARK-16779
Project: Spark
Issue Type: Sub-task
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holdenk updated SPARK-16773:
Summary: Post Spark 2.0 deprecation & warnings cleanup (was: Post Spark
2.0 deprecation cleanup)
> Post S
holdenk created SPARK-16778:
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Summary: Fix use of deprecated SQLContext constructor
Key: SPARK-16778
URL: https://issues.apache.org/jira/browse/SPARK-16778
Project: Spark
Issue Type: Sub-task
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holdenk updated SPARK-16775:
Component/s: SQL
> Reduce internal warnings from deprecated accumulator API
> -
holdenk created SPARK-16777:
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Summary: Parquet schema converter depends on deprecated APIs
Key: SPARK-16777
URL: https://issues.apache.org/jira/browse/SPARK-16777
Project: Spark
Issue Type: Sub-tas
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holdenk updated SPARK-16775:
Component/s: (was: ML)
(was: SQL)
(was: MLlib)
> Reduce inter
holdenk created SPARK-16776:
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Summary: Fix Kafka deprecation warnings
Key: SPARK-16776
URL: https://issues.apache.org/jira/browse/SPARK-16776
Project: Spark
Issue Type: Sub-task
Component
holdenk created SPARK-16775:
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Summary: Reduce internal warnings from deprecated accumulator API
Key: SPARK-16775
URL: https://issues.apache.org/jira/browse/SPARK-16775
Project: Spark
Issue Type: Su
holdenk created SPARK-16774:
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Summary: Fix use of deprecated TimeStamp constructor
Key: SPARK-16774
URL: https://issues.apache.org/jira/browse/SPARK-16774
Project: Spark
Issue Type: Sub-task
holdenk created SPARK-16773:
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Summary: Post Spark 2.0 deprecation cleanup
Key: SPARK-16773
URL: https://issues.apache.org/jira/browse/SPARK-16773
Project: Spark
Issue Type: Improvement
Co
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holdenk commented on SPARK-15130:
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Now that 2.0 is ready to go out, maybe we can decide w
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holdenk updated SPARK-16720:
Summary: Loading CSV file with 2k+ columns fails during attribute
resolution on action (was: Loading CSV f
holdenk created SPARK-16720:
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Summary: Loading CSV file with 2k+ columns and writing result with
one selected column fails during attribute resolution
Key: SPARK-16720
URL: https://issues.apache.org/jira/browse/SPARK-16
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holdenk commented on SPARK-16589:
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Yah I think we should explore whats going on a bit mor
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holdenk updated SPARK-15581:
Description:
This is a master list for MLlib improvements we are working on for the next
release. Please v
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holdenk commented on SPARK-14813:
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Yup, auditing is done and once 2.0 is out we will go b
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holdenk updated SPARK-16424:
Description:
For Spark 2.1 we should consider adding support for machine learning on top of
the structured
holdenk created SPARK-16454:
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Summary: Consider adding a per-batch transform for structured
streaming
Key: SPARK-16454
URL: https://issues.apache.org/jira/browse/SPARK-16454
Project: Spark
Issue T
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holdenk commented on SPARK-15581:
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Yah - the more I look at it the more rough it seems -
holdenk created SPARK-16424:
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Summary: Add support for Structured Streaming to the ML Pipeline
API
Key: SPARK-16424
URL: https://issues.apache.org/jira/browse/SPARK-16424
Project: Spark
Issue Type
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holdenk commented on SPARK-15581:
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What do we think of Streaming ML Pipelines being on th
holdenk created SPARK-16407:
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Summary: Allow users to supply custom StreamSinkProviders
Key: SPARK-16407
URL: https://issues.apache.org/jira/browse/SPARK-16407
Project: Spark
Issue Type: Improvemen
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https://issues.apache.org/jira/browse/SPARK-13233?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15356683#comment-15356683
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holdenk commented on SPARK-13233:
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The ability to intermix functional transformations eas
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holdenk commented on SPARK-13233:
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[~maver1ck] not really sure what the API plan is here
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holdenk commented on SPARK-16020:
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Do we know why this bug happened?
> Fix complete mode
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holdenk commented on SPARK-15954:
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See related PR https://github.com/apache/spark/pull/12
holdenk created SPARK-15954:
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Summary: TestHive has issues being used in PySpark
Key: SPARK-15954
URL: https://issues.apache.org/jira/browse/SPARK-15954
Project: Spark
Issue Type: Bug
Com
holdenk created SPARK-15902:
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Summary: Add a deprecation warning for Python 2.6
Key: SPARK-15902
URL: https://issues.apache.org/jira/browse/SPARK-15902
Project: Spark
Issue Type: Sub-task
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https://issues.apache.org/jira/browse/SPARK-12661?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15326393#comment-15326393
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holdenk commented on SPARK-12661:
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Even using pip on Python 2.6 prints a deprecation warn
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holdenk updated SPARK-15369:
Description: Transferring data from the JVM to the Python executor can be a
substantial bottleneck. While J
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holdenk commented on SPARK-12661:
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What are we missing to drop 2.6 support? We could keep
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holdenk commented on SPARK-15369:
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WIP design document
https://docs.google.com/document/
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holdenk updated SPARK-15623:
Component/s: PySpark
ML
> 2.0 python converage ml.feature
> --
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holdenk commented on SPARK-15625:
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This audit is complete (outstanding PRs and issue in p
holdenk created SPARK-15630:
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Summary: 2.0 python converage ml root module
Key: SPARK-15630
URL: https://issues.apache.org/jira/browse/SPARK-15630
Project: Spark
Issue Type: Improvement
C
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holdenk commented on SPARK-14813:
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I'm thinking we should skip read/write missing in comp
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holdenk commented on SPARK-15627:
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ml.tuning audit complete
> 2.0 python converage ml.tu
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holdenk commented on SPARK-15623:
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cc [~bryanc] can you just double check/confirm that yo
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holdenk updated SPARK-15628:
Component/s: PySpark
ML
> pyspark.ml.evaluation module
>
>
>
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holdenk commented on SPARK-15628:
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API Audit of this component complete
> pyspark.ml.eva
holdenk created SPARK-15628:
---
Summary: pyspark.ml.evaluation module
Key: SPARK-15628
URL: https://issues.apache.org/jira/browse/SPARK-15628
Project: Spark
Issue Type: Improvement
Report
holdenk created SPARK-15629:
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Summary: 2.0 python converage pyspark.ml.linalg
Key: SPARK-15629
URL: https://issues.apache.org/jira/browse/SPARK-15629
Project: Spark
Issue Type: Improvement
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https://issues.apache.org/jira/browse/SPARK-15589?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15304692#comment-15304692
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holdenk commented on SPARK-15589:
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Of course needs to wait for the Python Dataset API to
holdenk created SPARK-15627:
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Summary: 2.0 python converage ml.tuning module
Key: SPARK-15627
URL: https://issues.apache.org/jira/browse/SPARK-15627
Project: Spark
Issue Type: Improvement
holdenk created SPARK-15626:
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Summary: 2.0 python converage ml.regression module
Key: SPARK-15626
URL: https://issues.apache.org/jira/browse/SPARK-15626
Project: Spark
Issue Type: Improvement
holdenk created SPARK-15624:
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Summary: 2.0 python converage ml.recommendation module
Key: SPARK-15624
URL: https://issues.apache.org/jira/browse/SPARK-15624
Project: Spark
Issue Type: Improvement
holdenk created SPARK-15625:
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Summary: 2.0 python converage ml.classification module
Key: SPARK-15625
URL: https://issues.apache.org/jira/browse/SPARK-15625
Project: Spark
Issue Type: Improvement
holdenk created SPARK-15623:
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Summary: 2.0 python converage ml.feature
Key: SPARK-15623
URL: https://issues.apache.org/jira/browse/SPARK-15623
Project: Spark
Issue Type: Improvement
Rep
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holdenk commented on SPARK-14813:
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No worries, I'll break it up then.
> ML 2.0 QA: API:
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holdenk commented on SPARK-13233:
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So curious - is this targeted for 2.0 or are we planni
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holdenk commented on SPARK-12776:
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I think this might be duplicated by SPARK-13233, altho
holdenk created SPARK-15589:
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Summary: Anaylze simple PySpark closures and generate SQL
expressions
Key: SPARK-15589
URL: https://issues.apache.org/jira/browse/SPARK-15589
Project: Spark
Issue Typ
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https://issues.apache.org/jira/browse/SPARK-14813?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15303169#comment-15303169
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holdenk commented on SPARK-14813:
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I'd really like to split it up - but haven't heard bac
holdenk created SPARK-15577:
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Summary: Java can't import DataFrame type alias
Key: SPARK-15577
URL: https://issues.apache.org/jira/browse/SPARK-15577
Project: Spark
Issue Type: Improvement
holdenk created SPARK-15551:
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Summary: Scaladoc for KeyValueGroupedDataset points to old method
Key: SPARK-15551
URL: https://issues.apache.org/jira/browse/SPARK-15551
Project: Spark
Issue Type: Do
holdenk created SPARK-15412:
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Summary: Improve linear & isotonic regression methods PyDocs
Key: SPARK-15412
URL: https://issues.apache.org/jira/browse/SPARK-15412
Project: Spark
Issue Type: Improve
holdenk created SPARK-15369:
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Summary: Investigate selectively using Jython for parts of PySpark
Key: SPARK-15369
URL: https://issues.apache.org/jira/browse/SPARK-15369
Project: Spark
Issue Type: I
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holdenk updated SPARK-15316:
Description: PySpark's GeneralizedLinearRegression is missing the
linkPredictionCol param. (was: PySpark's
holdenk created SPARK-15316:
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Summary: PySpark GeneralizedLinearRegression missing
linkPredictionCol param
Key: SPARK-15316
URL: https://issues.apache.org/jira/browse/SPARK-15316
Project: Spark
Is
holdenk created SPARK-15281:
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Summary: PySpark ML GBTRegressor lacks impurity param
Key: SPARK-15281
URL: https://issues.apache.org/jira/browse/SPARK-15281
Project: Spark
Issue Type: Improvement
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https://issues.apache.org/jira/browse/SPARK-15061?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15280589#comment-15280589
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holdenk commented on SPARK-15061:
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Exciting "Py4J 0.10.1 has just been released on PyPI,
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holdenk commented on SPARK-14813:
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redid the links
> ML 2.0 QA: API: Python API coverage
holdenk created SPARK-15254:
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Summary: Improve ML pipeline Cross Validation Scaladoc & PyDoc
Key: SPARK-15254
URL: https://issues.apache.org/jira/browse/SPARK-15254
Project: Spark
Issue Type: Impro
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holdenk updated SPARK-15254:
Component/s: ML
> Improve ML pipeline Cross Validation Scaladoc & PyDoc
> -
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holdenk commented on SPARK-15194:
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So this is the ml api not the mllib api, ml's `Multiva
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holdenk updated SPARK-15194:
Description: We have a PySpark API for the MLLib version but not the ML
version. This would allow Python's
holdenk created SPARK-15195:
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Summary: Improve PyDoc for ml.tuning
Key: SPARK-15195
URL: https://issues.apache.org/jira/browse/SPARK-15195
Project: Spark
Issue Type: Improvement
Component
holdenk created SPARK-15194:
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Summary: Add Python ML API for MultivariateGaussian
Key: SPARK-15194
URL: https://issues.apache.org/jira/browse/SPARK-15194
Project: Spark
Issue Type: Improvement
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holdenk commented on SPARK-14813:
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[~yanboliang]Just following up since I've done a first
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holdenk updated SPARK-15189:
Component/s: Documentation
> ml.Evaluation pydoc issues
> --
>
> Ke
holdenk created SPARK-15189:
---
Summary: ml.Evaluation pydoc issues
Key: SPARK-15189
URL: https://issues.apache.org/jira/browse/SPARK-15189
Project: Spark
Issue Type: Improvement
Components
holdenk created SPARK-15188:
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Summary: NaiveBayes is missing Thresholds param
Key: SPARK-15188
URL: https://issues.apache.org/jira/browse/SPARK-15188
Project: Spark
Issue Type: Improvement
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https://issues.apache.org/jira/browse/SPARK-15136?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15273709#comment-15273709
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holdenk commented on SPARK-15136:
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Seems reasonable, I've closed the two sub-tasks and I'
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holdenk closed SPARK-15138.
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Resolution: Duplicate
> Linkify ML PyDoc regression
> ---
>
> Key: SP
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holdenk closed SPARK-15137.
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Resolution: Duplicate
> Linkify ML PyDoc classification
> ---
>
>
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holdenk commented on SPARK-15163:
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I think you were talking about https://issues.apache.o
holdenk created SPARK-15169:
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Summary: Consider improving HasSolver to allow generilization
Key: SPARK-15169
URL: https://issues.apache.org/jira/browse/SPARK-15169
Project: Spark
Issue Type: Improv
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holdenk updated SPARK-15168:
Description: MultilayerPerceptronClassifier is missing step size, solver,
and weights. Add these params. (
holdenk created SPARK-15168:
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Summary: Add missing params to Python's
MultilayerPerceptronClassifier
Key: SPARK-15168
URL: https://issues.apache.org/jira/browse/SPARK-15168
Project: Spark
Issue Ty
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https://issues.apache.org/jira/browse/SPARK-15163?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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holdenk updated SPARK-15163:
Component/s: PySpark
> Mark experimental algorithms experimental in PySpark
> -
holdenk created SPARK-15164:
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Summary: Mark classification algorithms as experimental where
marked so in scala
Key: SPARK-15164
URL: https://issues.apache.org/jira/browse/SPARK-15164
Project: Spark
holdenk created SPARK-15163:
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Summary: Mark experimental algorithms experimental in PySpark
Key: SPARK-15163
URL: https://issues.apache.org/jira/browse/SPARK-15163
Project: Spark
Issue Type: Improv
holdenk created SPARK-15162:
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Summary: Update PySpark LogisticRegression threshold PyDoc to be
as complete as Scaladoc
Key: SPARK-15162
URL: https://issues.apache.org/jira/browse/SPARK-15162
Project: Spark
[
https://issues.apache.org/jira/browse/SPARK-15138?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15272884#comment-15272884
]
holdenk commented on SPARK-15138:
-
cc [~yanboliang]
> Linkify ML PyDoc regression
>
holdenk created SPARK-15161:
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Summary: Consider moving featureImportances into TreeEnsemble
models base class
Key: SPARK-15161
URL: https://issues.apache.org/jira/browse/SPARK-15161
Project: Spark
[
https://issues.apache.org/jira/browse/SPARK-15161?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
holdenk updated SPARK-15161:
Component/s: ML
> Consider moving featureImportances into TreeEnsemble models base class
>
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