davidgasquez.com
📚 Personal bits of knowledge
📝 Add suggestion to fix ML model and encourage data gathering for metric impact in Kaggle-style competition
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Ideas.md
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Ideas.md
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- A distance metric is used to measure accuracy and value of the submitted datasets.
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- With enough participants, the final dataset could be a function of the best submissions (e.g: a vote where each row is decided as the most common submitted rows from top participants or the average between them)
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- Could also be another twist on Kaggle, mixing the ML competition aspects with Prediction Markets (e.g: polymarket).
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- [Fix the ML model, encourage participants to gather the data and measure based on the impact on the final metric](https://www.dataperf.org/training-set-acquisition).
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- Similar to Numerai, participants send submissions and stake some amount of money.
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- The best submissions are selected and the money is distributed among the participants depending on their stake.
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- For each task, rewards are given per row/prediction, not per model. This encourages a [[Plurality]] of models to be used that specialize in different tasks.