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Package org.apache.solr.ltr

This package contains the main logic for performing the reranking using a Learning to Rank model.

See: Description

Package org.apache.solr.ltr Description

This package contains the main logic for performing the reranking using a Learning to Rank model.

A model will be applied on each document through a LTRScoringQuery, a subclass of Query. As a normal query, the learned model will produce a new score for each document reranked.

A LTRScoringQuery is created by providing an instance of LTRScoringModel. An instance of LTRScoringModel defines how to combine the features in order to create a new score for a document. A new Learning to Rank model is plugged into the framework by extending LTRScoringModel, (see for example MultipleAdditiveTreesModel and LinearModel).

The LTRScoringQuery will take care of computing the values of all the features (see Feature) and then will delegate the final score generation to the LTRScoringModel, by calling the method score(float[] modelFeatureValuesNormalized).

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