Comments (2)
@EKMeyerson was suggesting computing the average rank across geos.
For instance:
predictor_1: ranks 3rd on Italy, 2nd on USA. Avg = 2.5
predictor_2: ranks 5th on Italy, 1st on USA. Avg = 3
=> predictor_1 ranks better than predictor_2.
I guess it's possible to compute a weighted average too, where the weight could be the population size of the geo.
from covid-xprize.
We have decided to go with Mean Rank (as Olivier has described above) for the main quantitative metric. This will be computed both across all regions and across specialty regions.
We will compute additional metrics, like MAE, and MAE per 100K cases as additional data useful to the judges.
from covid-xprize.
Related Issues (20)
- Update predictor_robojudge notebook to consider only the fixed list of countries
- Update scenario_generator notebook to generate the official IP file
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- Add population estimates for Washington DC and Virgin Islands
- Check Date column contains dates
- Ground truth missing for Washington DC HOT 2
- Add an example prescription model output HOT 1
- Fix shortsighted scenario_generator tests HOT 1
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- Provide a prescribe.py API
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- Provide the "standard" predictor to use for Phase 2 prescriptors evaluation
- Make prescriptors pip installable HOT 1
- Standard predictor is predicting from Jan 11, 2021 HOT 3
- Refactor notebooks to create `prescriptor_scoring` module
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from covid-xprize.