The weights you express could flag a probabilistic view or your final score. The model you quoted will calculate the final score as : 0.9*scorePersonalId +0.1* originalScore
The final score will NOT necessarily be 0<finalScore<1 . If that was not the case, I see little benefit in having the weights in a model to be passed at query time. The entire of LTR sense is to calculate those weights to optimise your ranking function, sure you can have multiple models, trained on different datasets, but each model will be the fixed ( and described by the json). If you want to play with weights you can potentially take a look to the ^= boost operator (which builds constant score queries) in cooperation with dismax/edismax[1] qf and different boosts. [1] https://lucene.apache.org/solr/guide/6_6/the-dismax-query-parser.html#the-dismax-query-parser ----- --------------- 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
