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re-order features, target, weights in docs
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docs/make.jl

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@@ -20,7 +20,7 @@ makedocs(
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"predict/transform" => "predict_transform.md",
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"Kinds of Target Proxy" => "kinds_of_target_proxy.md",
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"obs and Data Interfaces" => "obs.md",
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"target/weights/features" => "target_weights_features.md",
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"features/target/weights" => "features_target_weights.md",
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"Accessor Functions" => "accessor_functions.md",
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"Learner Traits" => "traits.md",
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],

docs/src/target_weights_features.md renamed to docs/src/features_target_weights.md

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# [`target`, `weights`, and `features`](@id input)
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# [`features`, `target`, and `weights`](@id input)
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Methods for extracting parts of training observations. Here "observations" means the
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output of [`obs(learner, data)`](@ref); if `obs` is not overloaded for `learner`, then
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"observations" is any `data` supported in calls of the form [`fit(learner, data)`](@ref)
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```julia
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LearnAPI.features(learner, observations) -> <training "features", suitable input for `predict` or `transform`>
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LearnAPI.target(learner, observations) -> <target variable>
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LearnAPI.weights(learner, observations) -> <per-observation weights>
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LearnAPI.features(learner, observations) -> <training "features", suitable input for `predict` or `transform`>
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```
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Here `data` is something supported in a call of the form `fit(learner, data)`.
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| method | fallback | compulsory? |
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|:----------------------------|:-----------------:|--------------------------|
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| [`LearnAPI.features`](@ref) | see docstring | if fallback insufficient |
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| [`LearnAPI.target`](@ref) | returns `nothing` | no |
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| [`LearnAPI.weights`](@ref) | returns `nothing` | no |
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| [`LearnAPI.features`](@ref) | see docstring | if fallback insufficient |
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# Reference
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```@docs
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LearnAPI.features
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LearnAPI.target
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LearnAPI.weights
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LearnAPI.features
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```

docs/src/reference.md

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@@ -183,8 +183,8 @@ Most learners will also implement [`predict`](@ref) and/or [`transform`](@ref).
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implement the observation access API specified by
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[`LearnAPI.data_interface(learner)`](@ref).
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- [`LearnAPI.target`](@ref input), [`LearnAPI.weights`](@ref input),
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[`LearnAPI.features`](@ref): for extracting relevant parts of training data, where
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- [`LearnAPI.features`](@ref input), [`LearnAPI.target`](@ref input),
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[`LearnAPI.weights`](@ref input): for extracting relevant parts of training data, where
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defined.
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- [Accessor functions](@ref accessor_functions): these include functions like

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