Hi 

Do you mean the test of significance that you usually get with R output? I 
don’t think there is anything implemented in the standard MLLib libraries 
however I believe that the sparkR version provides that. See 
http://spark.apache.org/docs/1.6.2/sparkr.html#gaussian-glm-model

-------------------------------------------------------------------------------
Robin East
Spark GraphX in Action Michael Malak and Robin East
Manning Publications Co.
http://www.manning.com/books/spark-graphx-in-action 
<http://www.manning.com/books/spark-graphx-in-action>





> On 4 Nov 2016, at 07:38, Carlo.Allocca <carlo.allo...@open.ac.uk> wrote:
> 
> Hi Mohit, 
> 
> Thank you for your reply. 
> OK. it means coefficient with high score are more important that other with 
> low score…
> 
> Many Thanks,
> Best Regards,
> Carlo
> 
> 
>> On 3 Nov 2016, at 20:41, Mohit Jaggi <mohitja...@gmail.com> wrote:
>> 
>> For linear regression, it should be fairly easy. Just sort the co-efficients 
>> :)
>> 
>> Mohit Jaggi
>> Founder,
>> Data Orchard LLC
>> www.dataorchardllc.com
>> 
>> 
>> 
>> 
>>> On Nov 3, 2016, at 3:35 AM, Carlo.Allocca <carlo.allo...@open.ac.uk> wrote:
>>> 
>>> Hi All,
>>> 
>>> I am using SPARK and in particular the MLib library.
>>> 
>>> import org.apache.spark.mllib.regression.LabeledPoint;
>>> import org.apache.spark.mllib.regression.LinearRegressionModel;
>>> import org.apache.spark.mllib.regression.LinearRegressionWithSGD;
>>> 
>>> For my problem I am using the LinearRegressionWithSGD and I would like to 
>>> perform a “Rank Features By Importance”.
>>> 
>>> I checked the documentation and it seems that does not provide such methods.
>>> 
>>> Am I missing anything?  Please, could you provide any help on this?
>>> Should I change the approach?
>>> 
>>> Many Thanks in advance,
>>> 
>>> Best Regards,
>>> Carlo
>>> 
>>> 
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> 
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