Project.toml

name = "EvoTrees"
uuid = "f6006082-12f8-11e9-0c9c-0d5d367ab1e5"
authors = ["jeremiedb <jeremie.db@evovest.com>"]
version = "0.17.2"

[deps]
BSON = "fbb218c0-5317-5bc6-957e-2ee96dd4b1f0"
CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
MLJModelInterface = "e80e1ace-859a-464e-9ed9-23947d8ae3ea"
NetworkLayout = "46757867-2c16-5918-afeb-47bfcb05e46a"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
RecipesBase = "3cdcf5f2-1ef4-517c-9805-6587b60abb01"
Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
Tables = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"

[weakdeps]
CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"

[extensions]
EvoTreesCUDAExt = "CUDA"

[compat]
BSON = "0.3"
CUDA = "3.0, 4.0, 5.0"
CategoricalArrays = "0.9, 0.10"
Distributions = "0.24, 0.25"
MLJModelInterface = "0.3, 0.4, 1.0"
NetworkLayout = "0.4"
Random = "1"
RecipesBase = "1"
Statistics = "1"
StatsBase = "0.32, 0.33, 0.34"
Tables = "1.9"
julia = "1.9"

[extras]
CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
MLJTestInterface = "72560011-54dd-4dc2-94f3-c5de45b75ecd"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

[targets]
test = ["CUDA", "DataFrames", "Test", "MLJBase", "MLJTestInterface"]