Results/Comparisons:
https://docs.google.com/document/d/1E0lwTCm-GDijJUjmfu_aA0EwuLCkm2B2rikJ2hoh-MM/edit
How to measure success/compare methods?
In the NSGA-II paper[1], there were two performance measures they used, neither were AUC. Since these models were widely used, they used 500 known, evenly distributed, points on the Pareto to measure the average distance from each resultant point to the Pareto, which was the first metric. The second metric was a measure of spread across the Pareto of the obtained solutions, calculated with a given algorithm.
REFERENCES:
[1] Kalyanmoy Deb, Associate Member, IEEE, Amrit Pratap, Sameer Agarwal, and T. Meyarivan, A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II, IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, VOL. 6, NO. 2, APRIL 2002
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