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- We propose that simple ordinal rank best predicts traits when competition is density-dependent, whereas proportional rank best predicts traits when competition is density-independent. We found that for 75% of traits (15/20), one rank metric performed better than the other.
royalsocietypublishing.org/doi/10.1098/rspb.2020.1013
Sep 9, 2020 · We propose that simple ordinal rank best predicts traits when competition is density-dependent, whereas proportional rank best predicts traits when competition is density-independent. We found that for 75% of traits (15/20), one rank metric performed better than the other.
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We propose that simple ordinal rank best predicts traits...
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Jul 2, 2015 · Three relevant metrics are top-k accuracy, precision@k and recall@k. The $k$ depends on your application. For all of them, for the ranking-queries you evaluate, the total number of relevant items should be above $k$. Top-k classification accuracy for ranking. For the ground truth, it might be hard to define an order.
Jul 29, 2023 · The best and worst possible rankings are shown on the left and on the right respectively. For simplicity, parameter p is chosen as 1. On the left, all the retrieved documents are sorted in the descending order of their relevance resulting in the best possible ERR .
We propose that simple ordinal rank best predicts traits when compe- tition is density-dependent, whereas proportional rank best predicts traits when competition is density-independent.
- Emily J Levy, Matthew N Zipple, Emily McLean, Fernando A Campos, Fernando A Campos, Mauna Dasari, Ar...
- 2020
You can use predictive metrics like accuracy or Precision at K or ranking metrics like NDCG, MRR, or MAP at K. To go beyond accuracy, you can use behavioral metrics like serendipity, novelty, or diversity of recommendations.
May 2, 2020 · We propose that ordinal rank best predicts outcomes when competition is density-dependent, while proportional rank best predicts outcomes when competition is density-independent.
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Which rank metric is best for predicting traits?
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Sep 9, 2020 · We found that for 75% of traits (15/20), one rank metric performed better than the other. Strikingly, all male traits were best predicted by simple ordinal rank, whereas female traits were evenly split between proportional and simple ordinal rank.
