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From Kenneth Chan <kenn...@apache.org>
Subject Re: Recommendation template, Implicit Feedback, only "buy" events
Date Sun, 05 Mar 2017 05:45:46 GMT
see ruby example here

http://predictionio.incubator.apache.org/datacollection/eventapi/#using-event-api

both python an ruby should have file exporter supported

On Tue, Feb 28, 2017 at 4:04 AM Kasper Bjerke <kasper.bjerke91@gmail.com>
wrote:

> Thank you for your response. I am having some issues with the Ruby SDK. I
> can't seem to find out how to include the eventTime parameter in the
> create_event function. Does anyone have experience importing lots of data
> to the app using Ruby? Is there an alternative to the FileExporter in
> python for Ruby?
>
> 16. feb. 2017 08:56 skrev "Kenneth Chan" <kenneth@apache.org>:
>
> 1. yes.
> try follow this to modify template to use trainImplicit
>
> http://predictionio.incubator.apache.org/templates/recommendation/training-with-implicit-preference/
>
> 2. just import event to PIO as
>  {
> event: buy
> entitiy: user
> entityId: uid
> targetEntity: article
> targetEntityId: article_id
> eventTime: time of the buy event
> }
>
>
> On Tue, Feb 14, 2017 at 2:42 AM, Kasper Bjerke <kasper.bjerke91@gmail.com>
> wrote:
>
> Hi
>
> I'm currently trying to set up PredictionIO with the standard
> Recommendation template as a project. I have 4 years of data, but the data
> I have can only qualify as "buy" events (I realise that each of the "buy"
> events can be interpreted as: first "view" then "buy") from E-commerce, so
> I have changed the code to match:
>
>
> http://predictionio.incubator.apache.org/templates/recommendation/training-with-implicit-preference/
>
> But instead of the sample "view" event I made it "buy". My questions are
> as follows:
>
> 1) Is it possible to use this template based off of only "buy" events?
> 2) And how should the testdata be formatted? Because all the examples I
> can find are based off of rating events: uid::movie_id::rating
>
> I was thinking: uid::article_id::"buy"? I'm fairly new to this, I have
> looked into Spark MLLib, but all the examples use the MovieLens dataset.
>
> Thank you,
> - Kasper
>
>
>

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