You are viewing a plain text version of this content. The canonical link for it is here.
Posted to user@spark.apache.org by Chandan Verma <ch...@citiustech.com> on 2016/01/06 19:45:49 UTC
Predictive Modelling in sparkR
Has anyone tried building logistic regression model in SparkR.. Is it
recommended? Does it take longer to do process than what can be done in
simple R?
===========================================================================================================================================================================================
DISCLAIMER:
The information contained in this message (including any attachments) is confidential and may be privileged. If you have received it by mistake please notify the sender by return e-mail and permanently delete this message and any attachments from your system. Any dissemination, use, review, distribution, printing or copying of this message in whole or in part is strictly prohibited. Please note that e-mails are susceptible to change. CitiusTech shall not be liable for the improper or incomplete transmission of the information contained in this communication nor for any delay in its receipt or damage to your system. CitiusTech does not guarantee that the integrity of this communication has been maintained or that this communication is free of viruses, interceptions or interferences.
====================================================================================================================================================================
Re: Predictive Modelling in sparkR
Posted by Chandan Verma <ch...@citiustech.com>.
Hi yanbo,
I was able to successfully perform logistic regression on my data and also performed the cross validation and it all worked fine.
Thanks
Sent from my Sony Xperia™ smartphone
---- Yanbo Liang wrote ----
>Hi Chandan,
>
>
>Do you mean to run your own LR algorithm based on SparkR?
>
>Actually, SparkR provide the ability to run the distributed Spark MLlib LR and the interface is similar with the R GLM.
>
>For your refer: https://spark.apache.org/docs/latest/sparkr.html#binomial-glm-model
>
>
>2016-01-07 2:45 GMT+08:00 Chandan Verma <ch...@citiustech.com>:
>
>Has anyone tried building logistic regression model in SparkR.. Is it recommended? Does it take longer to do process than what can be done in simple R?
>
>
>
>=========================================================================================================================================================================================== DISCLAIMER: The information contained in this message (including any attachments) is confidential and may be privileged. If you have received it by mistake please notify the sender by return e-mail and permanently delete this message and any attachments from your system. Any dissemination, use, review, distribution, printing or copying of this message in whole or in part is strictly prohibited. Please note that e-mails are susceptible to change. CitiusTech shall not be liable for the improper or incomplete transmission of the information contained in this communication nor for any delay in its receipt or damage to your system. CitiusTech does not guarantee that the integrity of this communication has been maintained or that this communication is free of viruses, interceptions or interferences. ====================================================================================================================================================================
>
>
===========================================================================================================================================================================================
DISCLAIMER:
The information contained in this message (including any attachments) is confidential and may be privileged. If you have received it by mistake please notify the sender by return e-mail and permanently delete this message and any attachments from your system. Any dissemination, use, review, distribution, printing or copying of this message in whole or in part is strictly prohibited. Please note that e-mails are susceptible to change. CitiusTech shall not be liable for the improper or incomplete transmission of the information contained in this communication nor for any delay in its receipt or damage to your system. CitiusTech does not guarantee that the integrity of this communication has been maintained or that this communication is free of viruses, interceptions or interferences.
====================================================================================================================================================================
Re: Predictive Modelling in sparkR
Posted by Yanbo Liang <yb...@gmail.com>.
Hi Chandan,
Do you mean to run your own LR algorithm based on SparkR?
Actually, SparkR provide the ability to run the distributed Spark MLlib LR
and the interface is similar with the R GLM.
For your refer:
https://spark.apache.org/docs/latest/sparkr.html#binomial-glm-model
2016-01-07 2:45 GMT+08:00 Chandan Verma <ch...@citiustech.com>:
> Has anyone tried building logistic regression model in SparkR.. Is it
> recommended? Does it take longer to do process than what can be done in
> simple R?
>
>
> ===========================================================================================================================================================================================
> DISCLAIMER: The information contained in this message (including any
> attachments) is confidential and may be privileged. If you have received it
> by mistake please notify the sender by return e-mail and permanently delete
> this message and any attachments from your system. Any dissemination, use,
> review, distribution, printing or copying of this message in whole or in
> part is strictly prohibited. Please note that e-mails are susceptible to
> change. CitiusTech shall not be liable for the improper or incomplete
> transmission of the information contained in this communication nor for any
> delay in its receipt or damage to your system. CitiusTech does not
> guarantee that the integrity of this communication has been maintained or
> that this communication is free of viruses, interceptions or interferences.
> ====================================================================================================================================================================
>
>