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From Sean Owen <so...@cloudera.com>
Subject Re: Question about mllib als's implicit training
Date Thu, 12 Feb 2015 23:13:45 GMT
Where there is no user-item interaction, you provide no interaction,
not an interaction with strength 0. Otherwise your input is fully
dense.

On Thu, Feb 12, 2015 at 11:09 PM, Crystal Xing <crystalxing06@gmail.com> wrote:
> Hi,
>
> I have some implicit rating data, such as the purchasing data.  I read the
> paper about the implicit training algorithm used in spark and it mentioned
> the for user-prodct pairs which do not have implicit rating data, such as no
> purchase, we need to provide the value as 0.
>
> This is different from explicit training where when we provide training
> data, for user-product pair without a rating, we just do not have them in
> the training data instead of adding a user-product pair with rating 0.
>
> Am I understand this correctly?
>
>  Or for implicit training implementation in spark, the missing data will be
> automatically filled out as zero and we do not need to add them in the
> training data set?
>
> Thanks,
>
> Crystal.

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