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Xiangrui Meng commented on SPARK-14831:
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+1 on `read.ml` and `write.ml`, which are
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Xiangrui Meng updated SPARK-14315:
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Assignee: Gayathri Murali
> GLMs model persistence in SparkR
>
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Xiangrui Meng updated SPARK-14314:
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Shepherd: Yanbo Liang
Assignee: Gayathri Murali
Target Version/s: 2.0.0
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Xiangrui Meng updated SPARK-14315:
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Target Version/s: 2.0.0
> GLMs model persistence in SparkR
>
>
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Xiangrui Meng updated SPARK-14315:
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Shepherd: Yanbo Liang
> GLMs model persistence in SparkR
>
>
>
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Xiangrui Meng resolved SPARK-14313.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12685
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Xiangrui Meng updated SPARK-14313:
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Assignee: Yanbo Liang
> AFTSurvivalRegression model persistence in SparkR
> ---
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Xiangrui Meng updated SPARK-14313:
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Target Version/s: 2.0.0
> AFTSurvivalRegression model persistence in SparkR
> -
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Xiangrui Meng resolved SPARK-14312.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12573
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Xiangrui Meng updated SPARK-14850:
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Priority: Blocker (was: Critical)
> VectorUDT/MatrixUDT should take primitive arrays without b
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Xiangrui Meng updated SPARK-14850:
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Affects Version/s: 1.5.2
> VectorUDT/MatrixUDT should take primitive arrays without boxing
> --
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Xiangrui Meng commented on SPARK-14850:
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Ran the following code with different Spar
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Xiangrui Meng commented on SPARK-14831:
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1. Please see my reply to Felix above for
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Xiangrui Meng commented on SPARK-14831:
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We have been trying to mimic existing R AP
Xiangrui Meng created SPARK-14850:
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Summary: VectorUDT/MatrixUDT should take primitive arrays without
boxing
Key: SPARK-14850
URL: https://issues.apache.org/jira/browse/SPARK-14850
Project: Spark
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Xiangrui Meng updated SPARK-14850:
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Description:
In SPARK-9390, we switched to use GenericArrayData to store indices and values
in
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Xiangrui Meng commented on SPARK-14314:
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Please hold until the naive Bayes one gets
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Xiangrui Meng updated SPARK-14831:
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Description:
In current master, we have 4 ML methods in SparkR:
{code:none}
glm(formula, famil
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Xiangrui Meng updated SPARK-14831:
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Description:
In current master, we have 4 ML methods in SparkR:
{code:none}
glm(formula, famil
Xiangrui Meng created SPARK-14831:
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Summary: Make ML APIs in SparkR consistent
Key: SPARK-14831
URL: https://issues.apache.org/jira/browse/SPARK-14831
Project: Spark
Issue Type: Improvement
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Xiangrui Meng resolved SPARK-14479.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12287
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Xiangrui Meng updated SPARK-14479:
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Assignee: Yanbo Liang
> GLM supports output link prediction
> -
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Xiangrui Meng commented on SPARK-7992:
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Thanks for making this work in the official r
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Xiangrui Meng updated SPARK-7992:
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Assignee: Jakob Odersky
> Hide private classes/objects in in generated Java API doc
>
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Xiangrui Meng resolved SPARK-7992.
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Resolution: Fixed
Fix Version/s: 2.0.0
> Hide private classes/objects in in generated Jav
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Xiangrui Meng updated SPARK-14312:
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Target Version/s: 2.0.0
> NaiveBayes model persistence in SparkR
>
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Xiangrui Meng updated SPARK-14312:
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Assignee: Yanbo Liang
> NaiveBayes model persistence in SparkR
> --
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Xiangrui Meng updated SPARK-14312:
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Shepherd: Xiangrui Meng
> NaiveBayes model persistence in SparkR
>
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https://issues.apache.org/jira/browse/SPARK-7264?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng updated SPARK-7264:
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Target Version/s: 2.0.0
> SparkR API for parallel functions
> -
>
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Xiangrui Meng updated SPARK-7264:
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Assignee: Timothy Hunter
> SparkR API for parallel functions
> -
>
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Xiangrui Meng updated SPARK-14299:
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Assignee: Xusen Yin
> Scala ML examples code merge and clean up
> -
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Xiangrui Meng resolved SPARK-14299.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12366
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Xiangrui Meng updated SPARK-14440:
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Assignee: Xusen Yin
> Remove PySpark ml.pipeline's specific Reader and Writer
> ---
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Xiangrui Meng resolved SPARK-14440.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12216
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Xiangrui Meng commented on SPARK-13944:
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`mllib-local` by the name is not scoped ju
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Xiangrui Meng updated SPARK-14657:
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Target Version/s: 2.0.0
> RFormula output wrong features when formula w/o intercept
> -
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Xiangrui Meng updated SPARK-14657:
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Shepherd: Xiangrui Meng
> RFormula output wrong features when formula w/o intercept
> -
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Xiangrui Meng updated SPARK-14657:
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Assignee: Yanbo Liang
> RFormula output wrong features when formula w/o intercept
> ---
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Xiangrui Meng updated SPARK-13925:
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Assignee: Yanbo Liang
> Expose R-like summary statistics in SparkR::glm for more family and lin
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Xiangrui Meng resolved SPARK-13925.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12393
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Xiangrui Meng resolved SPARK-14549.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12317
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Xiangrui Meng created SPARK-14653:
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Summary: Remove NumericParser and jackson dependency from
mllib-local
Key: SPARK-14653
URL: https://issues.apache.org/jira/browse/SPARK-14653
Project: Spark
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Xiangrui Meng resolved SPARK-14374.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12383
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Xiangrui Meng created SPARK-14646:
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Summary: k-means save/load should put one cluster per row
Key: SPARK-14646
URL: https://issues.apache.org/jira/browse/SPARK-14646
Project: Spark
Issue Type
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https://issues.apache.org/jira/browse/SPARK-12869?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng resolved SPARK-12869.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 10839
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Xiangrui Meng resolved SPARK-14565.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12360
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Xiangrui Meng commented on SPARK-13944:
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There are more production workflows using
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Xiangrui Meng commented on SPARK-14154:
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[~yuhaoyan] Thanks for the benchmark! I re
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Xiangrui Meng closed SPARK-14154.
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Resolution: Not A Problem
Fix Version/s: (was: 2.0.0)
> Simplify the implementation fo
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Xiangrui Meng commented on SPARK-14154:
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Changed the priority to critical since we
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Xiangrui Meng updated SPARK-14154:
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Priority: Critical (was: Minor)
> Simplify the implementation for Kolmogorov–Smirnov test
> --
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Xiangrui Meng updated SPARK-14568:
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Shepherd: Joseph K. Bradley
> Log instrumentation in logistic regression as a first task
>
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Xiangrui Meng updated SPARK-14568:
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Target Version/s: 2.0.0
> Log instrumentation in logistic regression as a first task
>
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Xiangrui Meng updated SPARK-14568:
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Assignee: Timothy Hunter
> Log instrumentation in logistic regression as a first task
> ---
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Xiangrui Meng commented on SPARK-14311:
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I think we can implement a generic load in
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Xiangrui Meng updated SPARK-14549:
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Shepherd: Xiangrui Meng
> Copy the Vector and Matrix classes from mllib to ml in mllib-local
>
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Xiangrui Meng resolved SPARK-14147.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 11958
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Xiangrui Meng updated SPARK-14147:
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Assignee: Yanbo Liang
> SparkR - ML predictors return features with vector datatype, however Sp
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Xiangrui Meng resolved SPARK-14563.
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Resolution: Fixed
Fix Version/s: 1.6.2
2.0.0
Issue resolved by pull
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Xiangrui Meng updated SPARK-13597:
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Assignee: Kai Jiang
> Python API for GeneralizedLinearRegression
>
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Xiangrui Meng resolved SPARK-13597.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 11468
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Xiangrui Meng resolved SPARK-13322.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 11365
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Xiangrui Meng updated SPARK-13590:
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Summary: Document the behavior of spark.ml logistic regression and AFT
survival regression when
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Xiangrui Meng updated SPARK-13590:
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Assignee: Yanbo Liang
> Document the behavior of spark.ml logistic regression when there are co
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Xiangrui Meng reopened SPARK-14154:
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Re-open this issue to continue discussion.
> Simplify the implementation for Kolmogorov–Smirnov
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Xiangrui Meng updated SPARK-14565:
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Description: Using regex is not robust and hard to maintain.
> RandomForest should use parseInt
Xiangrui Meng created SPARK-14565:
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Summary: RandomForest should use parseInt and parseDouble for
feature subset size instead of regexes
Key: SPARK-14565
URL: https://issues.apache.org/jira/browse/SPARK-14565
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Xiangrui Meng commented on SPARK-14154:
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[~yuhaoyan] The main purpose of the initia
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Xiangrui Meng resolved SPARK-14324.
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Resolution: Fixed
Fix Version/s: 2.0.0
> Refactor GLMs code in SparkRWrappers
> --
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Xiangrui Meng resolved SPARK-12566.
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Resolution: Fixed
Fix Version/s: 2.0.0
> GLM model family, link function support in Sp
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Xiangrui Meng updated SPARK-14563:
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Description:
`transformSchema` uses `__THIS__` as a temp table name, which would cause
errors
Xiangrui Meng created SPARK-14563:
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Summary: SQLTransformer.transformSchema is not implemented
correctly
Key: SPARK-14563
URL: https://issues.apache.org/jira/browse/SPARK-14563
Project: Spark
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https://issues.apache.org/jira/browse/SPARK-13600?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng resolved SPARK-13600.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 11553
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Xiangrui Meng updated SPARK-13322:
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Shepherd: Xiangrui Meng (was: DB Tsai)
> AFTSurvivalRegression should support feature standard
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Xiangrui Meng updated SPARK-14324:
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Assignee: Yanbo Liang
> Refactor GLMs code in SparkRWrappers
>
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Xiangrui Meng updated SPARK-12566:
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Shepherd: Xiangrui Meng (was: Yanbo Liang)
> GLM model family, link function support in SparkR
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https://issues.apache.org/jira/browse/SPARK-14462?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng resolved SPARK-14462.
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Resolution: Fixed
Issue resolved by pull request 12298
[https://github.com/apache/spark/pull/
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Xiangrui Meng updated SPARK-14510:
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Assignee: zhengruifeng
> Add args-checking for LDA and StreamingKMeans
> --
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Xiangrui Meng resolved SPARK-14510.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12062
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Xiangrui Meng updated SPARK-14510:
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Priority: Minor (was: Major)
> Add args-checking for LDA and StreamingKMeans
> ---
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Xiangrui Meng resolved SPARK-14500.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12274
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Xiangrui Meng updated SPARK-14497:
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Assignee: Feng Wang
> Use top instead of sortBy() to get top N frequent words as dict in
> Con
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Xiangrui Meng resolved SPARK-14497.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12265
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https://issues.apache.org/jira/browse/SPARK-14339?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng resolved SPARK-14339.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12063
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https://issues.apache.org/jira/browse/SPARK-14339?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng updated SPARK-14339:
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Assignee: zhengruifeng
> Add python examples for DCT,MinMaxScaler,MaxAbsScaler
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https://issues.apache.org/jira/browse/SPARK-14462?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng resolved SPARK-14462.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12241
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Xiangrui Meng created SPARK-14500:
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Summary: Accept Dataset[_] instead of DataFrame in MLlib APIs
Key: SPARK-14500
URL: https://issues.apache.org/jira/browse/SPARK-14500
Project: Spark
Issue
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https://issues.apache.org/jira/browse/SPARK-14305?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng updated SPARK-14305:
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Assignee: Yanbo Liang
> PySpark ml.clustering BisectingKMeans support export/import
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https://issues.apache.org/jira/browse/SPARK-14305?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng resolved SPARK-14305.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12112
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https://issues.apache.org/jira/browse/SPARK-14324?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng updated SPARK-14324:
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Assignee: (was: Yanbo Liang)
> Refactor GLMs code in SparkRWrappers
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https://issues.apache.org/jira/browse/SPARK-14303?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng resolved SPARK-14303.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12039
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https://issues.apache.org/jira/browse/SPARK-14324?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng updated SPARK-14324:
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Summary: Refactor GLMs code in SparkRWrappers (was: Refactor
SparkRWrappers)
> Refactor GLMs
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https://issues.apache.org/jira/browse/SPARK-14303?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng updated SPARK-14303:
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Summary: Refactor k-means code in SparkRWrappers (was: Refactor
SparkRWrappers)
> Refactor k-
Xiangrui Meng created SPARK-14324:
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Summary: Refactor SparkRWrappers
Key: SPARK-14324
URL: https://issues.apache.org/jira/browse/SPARK-14324
Project: Spark
Issue Type: Improvement
C
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https://issues.apache.org/jira/browse/SPARK-11262?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng resolved SPARK-11262.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 9229
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https://issues.apache.org/jira/browse/SPARK-14295?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng resolved SPARK-14295.
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Resolution: Fixed
Issue resolved by pull request 12088
[https://github.com/apache/spark/pull/
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https://issues.apache.org/jira/browse/SPARK-14274?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng resolved SPARK-14274.
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Resolution: Fixed
Issue resolved by pull request 12088
[https://github.com/apache/spark/pull/
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https://issues.apache.org/jira/browse/SPARK-14303?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng updated SPARK-14303:
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Assignee: Yanbo Liang
> Refactor SparkRWrappers
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>
> K
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https://issues.apache.org/jira/browse/SPARK-14313?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15220734#comment-15220734
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Xiangrui Meng commented on SPARK-14313:
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[~yanboliang] Are you interested working o
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https://issues.apache.org/jira/browse/SPARK-14314?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15220732#comment-15220732
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Xiangrui Meng commented on SPARK-14314:
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Hold until SPARK-14303 is done.
> K-means
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