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Project.toml
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32 lines (28 loc) · 884 Bytes
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name = "MLJScikitLearnInterface"
uuid = "5ae90465-5518-4432-b9d2-8a1def2f0cab"
authors = ["Thibaut Lienart, Anthony Blaom"]
version = "0.7.0"
[deps]
MLJModelInterface = "e80e1ace-859a-464e-9ed9-23947d8ae3ea"
PythonCall = "6099a3de-0909-46bc-b1f4-468b9a2dfc0d"
Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
Tables = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"
[compat]
Aqua = "0.8"
MLJBase = "1"
MLJModelInterface = "1.4"
MLJTestInterface = "0.2"
PythonCall = "0.9"
StableRNGs = "1"
Statistics = "1"
Tables = "1.10"
Test = "1"
julia = "1.6"
[extras]
Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
MLJTestInterface = "72560011-54dd-4dc2-94f3-c5de45b75ecd"
StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
[targets]
test = ["Aqua", "MLJBase", "MLJTestInterface", "StableRNGs", "Test"]