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README.md

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# MLJOpenML.jl
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| Linux | Coverage |
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| :-----------: | :------: |
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| [![Build status](https://github.com/JuliaAI/MLJOpenML.jl/workflows/CI/badge.svg)](https://github.com/JuliaAI/MLJOpenML.jl/actions)| [![codecov.io](http://codecov.io/github/JuliaAI/MLJOpenML.jl/coverage.svg?branch=master)](http://codecov.io/github/JuliaAI/MLJOpenML.jl?branch=master) |
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A package providing integration of [OpenML](https://www.openml.org) with the
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[MLJ](https://alan-turing-institute.github.io/MLJ.jl/dev/) machine
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learning framework.
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## Installation
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```julia
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using Pkg
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Pkg.add("MLJOpenML")
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```
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## Sample usage
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Load the iris data set from OpenML:
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```julia
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using MLJOpenML
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rowtable = MLJOpenML.load(61)
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```
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Convert to a `DataFrame`:
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```
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Pkg.add("DataFrames")
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using DataFrames
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df = DataFrame(rowtable)
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```
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## Documentation
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Documentation is provided in the [OpenML
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Integration](https://alan-turing-institute.github.io/MLJ.jl/dev/openml_integration/)
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section of the
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[MLJManual](https://alan-turing-institute.github.io/MLJ.jl/dev/)
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src/openml.jl

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using DataFrames
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rowtable = MLJOpenML.load(61);
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df = DataFrame(rowtable);
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using MLJ
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df2 = coerce(df, :class=>Multiclass)
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```
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"""

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