Model Based Comparison of Discounted Cumulative Gain and Average Precision
نویسندگان
چکیده
منابع مشابه
An apple-to-apple comparison of Learning-to-rank algorithms in terms of Normalized Discounted Cumulative Gain
The Normalized Discounted Cumulative Gain (NDCG) is a widely used evaluation metric for learning-to-rank (LTR) systems. NDCG is designed for ranking tasks with more than one relevance levels. There are many freely available, open source tools for computing the NDCG score for a ranked result list. Even though the definition of NDCG is unambiguous, the various tools can produce different scores f...
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ژورنال
عنوان ژورنال: Journal of Discrete Algorithms
سال: 2013
ISSN: 1570-8667
DOI: 10.1016/j.jda.2012.10.002