Alessandro Benedetti created SOLR-10449: -------------------------------------------
Summary: [LTR] Explain summarization improvement for LambdaMART Key: SOLR-10449 URL: https://issues.apache.org/jira/browse/SOLR-10449 Project: Solr Issue Type: Improvement Security Level: Public (Default Security Level. Issues are Public) Reporter: Alessandro Benedetti The current explain for the LambdaMART model is quite nice and human readable. But if you have big ensemble of trees and big trees, it becomes almost impossible to explain why document has a specific score. *Scenario* LambdaMART model with 100 trees, each tree quite tall A summarized explain in addition, could help. This could be as advanced as we want : Simple -> we fetch the features evaluated when scoring, and we return the most occurring ones Intermediate -> we return the most occurring features when scoring, highlighting the positive matches ( go RIGHT for binary features can be more relevant) Advanced -> we order first the trees by how much they influenced the final score and we add this information to the summary weighting differently the features. More advanced strategies are welcome, this could really help when explaining the score of a document running the lambdaMART model. -- This message was sent by Atlassian JIRA (v6.3.15#6346) --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org