ML Anthology

The Risk of Trivial Solutions in Bipartite Top Ranking

Aditya Krishna Menon
MLJ 2019 pp. 627-658
doi:10.1007/S10994-018-5759-4 /mlj/2019/menon2019mlj-risk/

Abstract

Given a sample of instances with binary labels, the bipartite top ranking problem is to produce a ranked list of instances whose head is dominated by positives. One popular existing approach to this problem is based on constructing surrogates to a performance measure known as the fraction of positives of the top (PTop). In this paper, we theoretically show that the measure and its surrogates have an undesirable property: for certain noisy distributions, it is optimal to trivially predict the same score for all instances . We propose a simple rectification which avoids such trivial solutions, while still focussing on the head of the ranked list and being as easy to optimise.

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Text

Menon. "The Risk of Trivial Solutions in Bipartite Top Ranking." Machine Learning, 2019. doi:10.1007/S10994-018-5759-4

Markdown

[Menon. "The Risk of Trivial Solutions in Bipartite Top Ranking." Machine Learning, 2019.](https://mlanthology.org/mlj/2019/menon2019mlj-risk/) doi:10.1007/S10994-018-5759-4

BibTeX

@article{menon2019mlj-risk,
  title     = {{The Risk of Trivial Solutions in Bipartite Top Ranking}},
  author    = {Menon, Aditya Krishna},
  journal   = {Machine Learning},
  year      = {2019},
  pages     = {627-658},
  doi       = {10.1007/S10994-018-5759-4},
  volume    = {108},
  url       = {https://mlanthology.org/mlj/2019/menon2019mlj-risk/}
}