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Core functionality for the MLJ machine learning framework
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JuliaAI/MLJBase.jl
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Repository for developers that provides core functionality for theMLJ machinelearning framework.
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master | v1 |  |  |
dev | v1 |  |  |
MLJ is a Juliaframework for combining and tuning machine learning models. Thisrepository provides core functionality for MLJ, including:
completing the functionality for methods defined "minimally" inMLJ's light-weight model interfaceMLJModelInterface (/src/interface)
definition ofmachines and their associated methods, such as
fit!andpredict/transform(src/machines).MLJ'smodel composition interface, includinglearningnetworks,pipelines,stacks,target transforms (/src/composition)
basic utilities formanipulating datasets and forsynthesizing datasets (src/data)
asmallinterfaceforresampling strategies and implementations, including
CV(),StratifiedCVandHoldout(src/resampling.jl). Actual performance evaluation measures (aka metrics), which previouslywere provided by MLJBase.jl, now live inStatisticalMeasures.jl.methods forperformance evaluation, based on those resampling strategies (src/resampling.jl)
one-dimensional hyperparameter range types, constructors andassociated methods, for use withMLJTuning (src/hyperparam)
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Core functionality for the MLJ machine learning framework