Skip to content

Commit

Permalink
Update Metadata to explain interpolation.
Browse files Browse the repository at this point in the history
  • Loading branch information
nikosbosse authored Dec 3, 2024
1 parent f31edec commit f20be4f
Showing 1 changed file with 2 additions and 2 deletions.
4 changes: 2 additions & 2 deletions model-metadata/Metaculus-cp.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -21,8 +21,8 @@ repo_url: "https://github.com/Metaculus/respiratory-diseases"
license: "CC-BY-4.0"
designated_model: true
team_funding: "This project is supported by the National Science Foundation under Award No. 2438211. Any opinions, findings and conclusions or recommendations expressed in this project are those of Metaculus and our forecasters, and do not necessarily reflect the views of the National Science Foundation."
methods: "A recency-weighted average of predictions made by forecasters on the Metaculus prediction platform."
data_inputs: "Users are allowed to make use of any data they choose. The recency-weighted average takes only the numeric forecasts made by forecasters on the platform into account."
methods: "A recency-weighted average of predictions made by forecasters on the Metaculus prediction platform. Missing forecasts are linearly interpolated."
data_inputs: "Users are allowed to make use of any data they choose. The recency-weighted average takes only the numeric forecasts made by forecasters on the platform into account. We only launch new questions every 2 weeks. This means that alternatingly, only the forecasts 1, 3, 5 or 0, 2, 4 will actually be available. Missing forecasts are linearly interpolated to always produce a set for horizons 1, 2, 3, 4."
methods_long: "The Metaculus Community Prediction is a consensus of recent forecaster predictions. It is designed to respond to big changes in forecaster opinion while still being fairly insensitive to outliers. For every forecaster, on ly their most recent prediction is kept. Predictions are assigned a number n, from oldest to newest (oldest is 1). Every prediction is weighted proportional to exp(sqrt(n)). Predictions are then aggregated by creating a mixture distribution of all available weighted forecasts."
ensemble_of_models: true
ensemble_of_hub_models: false

0 comments on commit f20be4f

Please sign in to comment.