What is the most appropriate approach to handle queries when splitting data when evaluating learning to rank models?
How data splitting can be done and why it is important for the offline evaluation of Learning to Rank models?
Tips and tricks to find out efficient and fast ways to read and parse a big JSON file in Python using real-world application
Tips and tricks to find out efficient and fast ways to read and parse a big JSON file in Python using real-world application
Query-level features and under-sampled queries, how to handle them? Find it out, with our new Learning to Rank implementations
Introduction With Rated Ranking Evaluator Enterprise approaching soon, we take the occasion of explaining in details why Offline Search Quality Evaluation is so important nowadays and what you can do already with the Rated Ranking Evaluator open-source libraries.More news will come soon as we are approaching the V1 release date.Stay tuned! Search Quality Evaluation Evaluation…