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Project.toml
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Project.toml
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name = "MLJ"
uuid = "add582a8-e3ab-11e8-2d5e-e98b27df1bc7"
authors = ["Anthony D. Blaom <anthony.blaom@gmail.com>"]
version = "0.20.7"
[deps]
CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
ComputationalResources = "ed09eef8-17a6-5b46-8889-db040fac31e3"
Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"
Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
FeatureSelection = "33837fe5-dbff-4c9e-8c2f-c5612fe2b8b6"
LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
MLJBalancing = "45f359ea-796d-4f51-95a5-deb1a414c586"
MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
MLJEnsembles = "50ed68f4-41fd-4504-931a-ed422449fee0"
MLJFlow = "7b7b8358-b45c-48ea-a8ef-7ca328ad328f"
MLJIteration = "614be32b-d00c-4edb-bd02-1eb411ab5e55"
MLJModels = "d491faf4-2d78-11e9-2867-c94bc002c0b7"
MLJTuning = "03970b2e-30c4-11ea-3135-d1576263f10f"
OpenML = "8b6db2d4-7670-4922-a472-f9537c81ab66"
Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
ProgressMeter = "92933f4c-e287-5a05-a399-4b506db050ca"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
ScientificTypes = "321657f4-b219-11e9-178b-2701a2544e81"
StatisticalMeasures = "a19d573c-0a75-4610-95b3-7071388c7541"
Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
Tables = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"
[compat]
CategoricalArrays = "0.8,0.9, 0.10"
ComputationalResources = "0.3"
Distributions = "0.21,0.22,0.23, 0.24, 0.25"
FeatureSelection = "0.2"
MLJBalancing = "0.1"
MLJBase = "1.5"
MLJEnsembles = "0.4"
MLJFlow = "0.5"
MLJIteration = "0.6"
MLJModels = "0.17"
MLJTestIntegration = "0.5.0"
MLJTuning = "0.8"
OpenML = "0.2,0.3"
Pkg = "<0.0.1, 1"
ProgressMeter = "1.1"
Random = "<0.0.1, 1"
Reexport = "1.2"
ScientificTypes = "3"
StatisticalMeasures = "0.1"
Statistics = "<0.0.1, 1"
StatsBase = "0.32,0.33, 0.34"
Tables = "0.2,1.0"
julia = "1.6"
[extras]
BetaML = "024491cd-cc6b-443e-8034-08ea7eb7db2b"
CatBoost = "e2e10f9a-a85d-4fa9-b6b2-639a32100a12"
EvoLinear = "ab853011-1780-437f-b4b5-5de6f4777246"
EvoTrees = "f6006082-12f8-11e9-0c9c-0d5d367ab1e5"
Imbalance = "c709b415-507b-45b7-9a3d-1767c89fde68"
InteractiveUtils = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
LightGBM = "7acf609c-83a4-11e9-1ffb-b912bcd3b04a"
MLJClusteringInterface = "d354fa79-ed1c-40d4-88ef-b8c7bd1568af"
MLJDecisionTreeInterface = "c6f25543-311c-4c74-83dc-3ea6d1015661"
MLJFlux = "094fc8d1-fd35-5302-93ea-dabda2abf845"
MLJGLMInterface = "caf8df21-4939-456d-ac9c-5fefbfb04c0c"
MLJLIBSVMInterface = "61c7150f-6c77-4bb1-949c-13197eac2a52"
MLJLinearModels = "6ee0df7b-362f-4a72-a706-9e79364fb692"
MLJMultivariateStatsInterface = "1b6a4a23-ba22-4f51-9698-8599985d3728"
MLJNaiveBayesInterface = "33e4bacb-b9e2-458e-9a13-5d9a90b235fa"
MLJScikitLearnInterface = "5ae90465-5518-4432-b9d2-8a1def2f0cab"
MLJTSVDInterface = "7fa162e1-0e29-41ca-a6fa-c000ca4e7e7e"
MLJTestIntegration = "697918b4-fdc1-4f9e-8ff9-929724cee270"
MLJTestInterface = "72560011-54dd-4dc2-94f3-c5de45b75ecd"
MLJText = "5e27fcf9-6bac-46ba-8580-b5712f3d6387"
MLJXGBoostInterface = "54119dfa-1dab-4055-a167-80440f4f7a91"
Markdown = "d6f4376e-aef5-505a-96c1-9c027394607a"
NearestNeighborModels = "636a865e-7cf4-491e-846c-de09b730eb36"
OneRule = "90484964-6d6a-4979-af09-8657dbed84ff"
OutlierDetectionNeighbors = "51249a0a-cb36-4849-8e04-30c7f8d311bb"
OutlierDetectionPython = "2449c660-d36c-460e-a68b-92ab3c865b3e"
ParallelKMeans = "42b8e9d4-006b-409a-8472-7f34b3fb58af"
PartialLeastSquaresRegressor = "f4b1acfe-f311-436c-bb79-8483f53c17d5"
PartitionedLS = "19f41c5e-8610-11e9-2f2a-0d67e7c5027f"
SIRUS = "cdeec39e-fb35-4959-aadb-a1dd5dede958"
SelfOrganizingMaps = "ba4b7379-301a-4be0-bee6-171e4e152787"
StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
Suppressor = "fd094767-a336-5f1f-9728-57cf17d0bbfb"
SymbolicRegression = "8254be44-1295-4e6a-a16d-46603ac705cb"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
[targets]
test = [
"BetaML",
"CatBoost",
"EvoLinear",
"EvoTrees",
"Imbalance",
"InteractiveUtils",
"LightGBM",
"MLJClusteringInterface",
"MLJDecisionTreeInterface",
"MLJFlux",
"MLJGLMInterface",
"MLJLIBSVMInterface",
"MLJLinearModels",
"MLJMultivariateStatsInterface",
"MLJNaiveBayesInterface",
"MLJScikitLearnInterface",
"MLJTSVDInterface",
"MLJTestInterface",
"MLJTestIntegration",
"MLJText",
"MLJXGBoostInterface",
"Markdown",
"NearestNeighborModels",
"OneRule",
"OutlierDetectionNeighbors",
"OutlierDetectionPython",
"ParallelKMeans",
"PartialLeastSquaresRegressor",
"PartitionedLS",
"SelfOrganizingMaps",
"SIRUS",
"SymbolicRegression",
"StableRNGs",
"Suppressor",
"Test",
]