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From prateek.agarwal@bigbasket.com <prateek.agar...@bigbasket.com>
Subject Re: Regarding LTR feature
Date Fri, 04 May 2018 06:24:33 GMT
Thanks again Alessandro

I tried with the feature and the Minmax normalizer you told.But then there is a slight problem
with the params in normalization. I don't really know the range(Min, Max) of values the payload_score
outputs and they are different for different queries.

I even tried looking at the source code to see if there is a way I can override a class so
that it iterates over all the re-ranked documents and calculate Max and min there itself and
pass it to MinMax normalizer class but it seems it's not possible.

Your help will really appreciated.

Thanks



Regards,
Prateek



On 2018/05/03 14:00:00, Alessandro Benedetti <a.benedetti@sease.io> wrote: 
> Mmmm, first of all, you know that each Solr feature is calculated per
> document right ?
> So you want to calculate the payload score for the document you are
> re-ranking, based on the query ( your External Feature Information) and
> normalize across the different documents?
> 
> I would go with this feature and use the normalization LTR functionality :
> 
> { 
>   "store" : "my_feature_store", 
>   "name" : "in_aggregated_terms", 
>   "class" : "org.apache.solr.ltr.feature.SolrFeature", 
>   "params" : { "q" : "{!payload_score 
> f=aggregated_terms func=max v=${query}}" } 
> } 
> 
> Then in the model you specify something like :
> 
> "name" : "myModelName",
>    "features" : [
>        {
>          "name" : "isBook"
>        },
> ...
>        {
>          "name" : "in_aggregated_terms",
>          "norm": {
>              "class" : "org.apache.solr.ltr.norm.MinMaxNormalizer",
>              "params" : { "min":"x", "max":"y" }
>          }
>        },
>        }
> 
> Give it a try, let me know
> 
> 
> 
> 
> -----
> ---------------
> Alessandro Benedetti
> Search Consultant, R&D Software Engineer, Director
> Sease Ltd. - www.sease.io
> --
> Sent from: http://lucene.472066.n3.nabble.com/Solr-User-f472068.html
> 

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