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docs/src/common_implementation_patterns.md

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re-executed for each new data set (do not generalize), but which have hyperparameters
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and/or deliver ancillary information about the computation.
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- [Ensemble Algorithms](@ref): Algorithms that blend predictions of multiple algorithms
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- [Ensembling](@ref): Algorithms that blend predictions of multiple algorithms
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- Time Series Forecasting
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# Ensemble Algorithms
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# Ensembling
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See [this
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example](https://github.com/JuliaAI/LearnAPI.jl/blob/dev/test/integration/iterative_algorithms.jl)
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example](https://github.com/JuliaAI/LearnAPI.jl/blob/dev/test/integration/ensembling.jl)
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from tests.

docs/src/patterns/incremental_algorithms.md

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docs/src/patterns/incremental_models.md

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# Iterative Algorithms
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See [this
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example](https://github.com/JuliaAI/LearnAPI.jl/blob/dev/test/integration/ensembling.jl)
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from tests.
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# Meta-algorithms
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Many meta-algorithms are wrappers. An example is [this bagged ensemble
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algorithm](https://github.com/JuliaAI/LearnAPI.jl/blob/dev/test/integration/iterative_algorithms.jl)
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Many meta-algorithms are can be implemented as wrappers. An example is [this bagged
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ensemble
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algorithm](https://github.com/JuliaAI/LearnAPI.jl/blob/dev/test/integration/ensembling.jl)
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from tests.
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