[jira] [Assigned] (SPARK-13449) Naive Bayes wrapper in SparkR

2016-03-02 Thread Apache Spark (JIRA)

 [ 
https://issues.apache.org/jira/browse/SPARK-13449?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Apache Spark reassigned SPARK-13449:


Assignee: Xusen Yin  (was: Apache Spark)

> Naive Bayes wrapper in SparkR
> -
>
> Key: SPARK-13449
> URL: https://issues.apache.org/jira/browse/SPARK-13449
> Project: Spark
>  Issue Type: New Feature
>  Components: ML, SparkR
>Reporter: Xiangrui Meng
>Assignee: Xusen Yin
>
> Following SPARK-13011, we can add a wrapper for naive Bayes in SparkR. R's 
> naive Bayes implementation is from package e1071 with signature:
> {code}
> ## S3 method for class 'formula'
> naiveBayes(formula, data, laplace = 0, ..., subset, na.action = na.pass)
> ## Default S3 method, which we don't want to support
> # naiveBayes(x, y, laplace = 0, ...)
> ## S3 method for class 'naiveBayes'
> predict(object, newdata,
>   type = c("class", "raw"), threshold = 0.001, eps = 0, ...)
> {code}
> It should be easy for us to match the parameters.



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[jira] [Assigned] (SPARK-13449) Naive Bayes wrapper in SparkR

2016-03-02 Thread Apache Spark (JIRA)

 [ 
https://issues.apache.org/jira/browse/SPARK-13449?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Apache Spark reassigned SPARK-13449:


Assignee: Apache Spark  (was: Xusen Yin)

> Naive Bayes wrapper in SparkR
> -
>
> Key: SPARK-13449
> URL: https://issues.apache.org/jira/browse/SPARK-13449
> Project: Spark
>  Issue Type: New Feature
>  Components: ML, SparkR
>Reporter: Xiangrui Meng
>Assignee: Apache Spark
>
> Following SPARK-13011, we can add a wrapper for naive Bayes in SparkR. R's 
> naive Bayes implementation is from package e1071 with signature:
> {code}
> ## S3 method for class 'formula'
> naiveBayes(formula, data, laplace = 0, ..., subset, na.action = na.pass)
> ## Default S3 method, which we don't want to support
> # naiveBayes(x, y, laplace = 0, ...)
> ## S3 method for class 'naiveBayes'
> predict(object, newdata,
>   type = c("class", "raw"), threshold = 0.001, eps = 0, ...)
> {code}
> It should be easy for us to match the parameters.



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