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rename Continuous -> Interpolated
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docs/src/traits.md

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@@ -82,7 +82,7 @@ requires:
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non-empty) this requirement is dropped.
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2. *Low level deserializability:* It should be possible to evaluate the trait *value* when
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`LearnAPI` is the only imported module.
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`LearnAPI` and `ScientificTypesBase` are the only imported modules.
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Because of 1, combining a lot of functionality into one learner (e.g. the learner can
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perform both classification or regression) can mean traits are necessarily less

src/types.jl

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@@ -42,7 +42,7 @@ See also [`LearnAPI.KindOfProxy`](@ref).
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| `SurvivalDistribution` | probability distribution for survival time |
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| `SurvivalHazardFunction` | hazard function for survival time |
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| `OutlierScore` | numerical score reflecting degree of outlierness (not necessarily normalized) |
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| `Continuous` | real-valued approximation/interpolation of a discrete-valued target, such as a count (e.g., number of phone calls) |
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| `Interpolated` | real-valued approximation/interpolation of a discrete-valued target, such as a count (e.g., number of phone calls) |
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¹Provided for completeness but discouraged to avoid [ambiguities in
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representation](https://github.com/alan-turing-institute/MLJ.jl/blob/dev/paper/paper.md#a-unified-approach-to-probabilistic-predictions-and-their-evaluation).
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:SurvivalDistribution,
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:HazardFunction,
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:OutlierScore,
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:Continuous,
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:Interpolated,
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:Quantile,
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:Expectile,
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]

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