Created
May 20, 2022 17:21
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`logScore` organization proposal
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| // Needs to be able to import `PointSetTypes.pointSetDist` as `t` | |
| type scoreArgs = DistDist(t, t) | DistFloat(t, float), DistDistDist(t, t, t), DistFloatDist(t, float, t) | |
| // Can be expanded for the other 4 cases of the definition of scoring a scalar prediction against a dist answer. | |
| module KlDivergence = { | |
| ... | |
| } | |
| module LogScoreAgainstScalarAnswer = { | |
| let score = (prediction, answer) => ... | |
| let scoreWithPrior = (prediction, answer, prior) => ... | |
| } | |
| module T = { | |
| let score = (args: scoreArgs) => | |
| switch args { | |
| DistDist(prediction, answer) => KlDivergence.score(prediction, answer) | |
| DistFloat(prediction, answer) => LogScoreAgainstScalarAnswer.score(prediction, answer) | |
| DistDistDist(prediction, answer, prior) => KlDivergence.score(prediction, answer) - KlDivergence.score(prior, answer) | |
| DistFloatDist(prediction, answer, prior) => LogScoreAgainstScalarAnswer.scoreWithPrior(prediction, answer, prior) | |
| } | |
| } |
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I don't see much of that here, but I'm happy for the scoring file to be dependent on PoitnSetTypes.pointSetDist, if that's what you mean.