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cuongnc220592 avatar cuongnc220592 commented on September 22, 2024
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ilariapet avatar ilariapet commented on September 22, 2024

Hi @cuongnc220592,

We have trained the model using the LambdaMART algorithm, where the final predicted score is the weighted sum of the prediction of each regression tree in the ensemble.

So the output of the model is an arbitrary score that doesnโ€™t reflect the relevance labels (test labels) we use in training/test sets but it is just a measure of how relevant the document was for that query and therefore an indicator of relative ordering between documents.

Consider an example where for a given query you have 4 documents:

Schermata 2022-03-29 alle 13 57 06

You use the predicted scores to sort descending the documents in order to obtain the ranking predicted by the model:

Schermata 2022-03-29 alle 13 57 14

Then the NDCG is computed using the relevance labels.

from learning-to-rank-spotify.

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