Merge remote-tracking branch 'origin/master' into export-serializable

JuliaAI · Oct 26, 2022 · 02bd898 · 02bd898
2 parents c165e34 + 212dcf6
commit 02bd898
Showing 1 changed file with 25 additions and 25 deletions.
diff --git a/docs/src/list_of_supported_models.md b/docs/src/list_of_supported_models.md
@@ -25,31 +25,31 @@ independent assessment.
 * *high*: indicates the package is very mature and functionalities are
   expected to have been fairly optimiser and tested.
 
-| Package | Models | Maturity | Note
-| ------- | ------ | -------- | ----
-[BetaML.jl](https://github.com/sylvaticus/BetaML.jl) | LinearPerceptron, KernelPerceptron, Pegasos, DecisionTreeClassifier, DecisionTreeRegressor,RandomForestClassifier, RandomForestRegressor, NeuralNetworkRegressor, MultitargetNeuralNetworkRegressor, NeuralNetworkClassifier, GaussianMixtureRegressor, MultitargetGaussianMixtureRegressor, KMeans, KMedoids, GaussianMixtureClusterer, SimpleImputer, GaussianMixtureImputer, MultitargetGaussianMixtureImputer, RandomForestImputer, GeneralImputer | medium |
-[Clustering.jl](https://github.com/JuliaStats/Clustering.jl) | KMeans, KMedoids | high | †
-[DecisionTree.jl](https://github.com/bensadeghi/DecisionTree.jl) | DecisionTreeClassifier, DecisionTreeRegressor, AdaBoostStumpClassifier, RandomForestClassifier, RandomForestRegressor | high | 
-[EvoTrees.jl](https://github.com/Evovest/EvoTrees.jl) | EvoTreeRegressor, EvoTreeClassifier, EvoTreeCount, EvoTreeGaussian | medium | gradient boosting models
-[GLM.jl](https://github.com/JuliaStats/GLM.jl) | LinearRegressor, LinearBinaryClassifier, LinearCountRegressor | medium | †
-[LIBSVM.jl](https://github.com/mpastell/LIBSVM.jl) | LinearSVC, SVC, NuSVC, NuSVR, EpsilonSVR, OneClassSVM | high | also via ScikitLearn.jl
-[LightGBM.jl](https://github.com/IQVIA-ML/LightGBM.jl) | LGBMClassifier, LGBMRegressor | high | 
-[MLJFlux.jl](https://github.com/FluxML/MLJFlux.jl) | NeuralNetworkRegressor, NeuralNetworkClassifier, MultitargetNeuralNetworkRegressor, ImageClassifier | low |
-[MLJLinearModels.jl](https://github.com/JuliaAI/MLJLinearModels.jl) | LinearRegressor, RidgeRegressor, LassoRegressor, ElasticNetRegressor, QuantileRegressor, HuberRegressor, RobustRegressor, LADRegressor, LogisticClassifier, MultinomialClassifier | medium |
-[MLJModels.jl](https://github.com/JuliaAI/MLJModels.jl) (built-in) | StaticTransformer, FeatureSelector, FillImputer, UnivariateStandardizer, Standardizer, UnivariateBoxCoxTransformer, OneHotEncoder, ContinuousEncoder, ConstantRegressor, ConstantClassifier, BinaryThreshholdPredictor | medium |
-[MLJText.jl](https://github.com/JuliaAI/MLJText.jl) | TfidfTransformer, BM25Transformer, CountTransformer | low |
-[MultivariateStats.jl](https://github.com/JuliaStats/MultivariateStats.jl) | LinearRegressor, MultitargetLinearRegressor, RidgeRegressor, MultitargetRidgeRegressor, PCA, KernelPCA, ICA, LDA, BayesianLDA, SubspaceLDA, BayesianSubspaceLDA, FactorAnalysis, PPCA | high | 
-[NaiveBayes.jl](https://github.com/dfdx/NaiveBayes.jl) | GaussianNBClassifier, MultinomialNBClassifier, HybridNBClassifier | low |
-[NearestNeighborModels.jl](https://github.com/JuliaAI/NearestNeighborModels.jl) | KNNClassifier, KNNRegressor, MultitargetKNNClassifier, MultitargetKNNRegressor | high |
-[OneRule.jl](https://github.com/roland-KA/OneRule.jl) | OneRuleClassifier | experimental |
-[OutlierDetectionNeighbors.jl](https://github.com/OutlierDetectionJL/OutlierDetectionNeighbors.jl) | ABODDetector, COFDetector, DNNDetector, KNNDetector, LOFDetector | medium | 
-[OutlierDetectionNetworks.jl](https://github.com/OutlierDetectionJL/OutlierDetectionNetworks.jl) | AEDetector, DSADDetector, ESADDetector | medium | 
-[OutlierDetectionPython.jl](https://github.com/OutlierDetectionJL/OutlierDetectionPython.jl) | ABODDetector, CBLOFDetector, COFDetector, COPODDetector, HBOSDetector, IForestDetector, KNNDetector, LMDDDetector, LOCIDetector, LODADetector, LOFDetector, MCDDetector, OCSVMDetector, PCADetector, RODDetector, SODDetector, SOSDetector | high | 
-[ParallelKMeans.jl](https://github.com/PyDataBlog/ParallelKMeans.jl) | KMeans | experimental |
-[PartialLeastSquaresRegressor.jl](https://github.com/lalvim/PartialLeastSquaresRegressor.jl) | PLSRegressor, KPLSRegressor | experimental |
-[ScikitLearn.jl](https://github.com/cstjean/ScikitLearn.jl) | ARDRegressor, AdaBoostClassifier, AdaBoostRegressor, AffinityPropagation, AgglomerativeClustering, BaggingClassifier, BaggingRegressor, BayesianLDA, BayesianQDA, BayesianRidgeRegressor, BernoulliNBClassifier, Birch, ComplementNBClassifier, DBSCAN, DummyClassifier, DummyRegressor, ElasticNetCVRegressor, ElasticNetRegressor, ExtraTreesClassifier, ExtraTreesRegressor, FeatureAgglomeration, GaussianNBClassifier, GaussianProcessClassifier, GaussianProcessRegressor, GradientBoostingClassifier, GradientBoostingRegressor, HuberRegressor, KMeans, KNeighborsClassifier, KNeighborsRegressor, LarsCVRegressor, LarsRegressor, LassoCVRegressor, LassoLarsCVRegressor, LassoLarsICRegressor, LassoLarsRegressor, LassoRegressor, LinearRegressor, LogisticCVClassifier, LogisticClassifier, MeanShift, MiniBatchKMeans, MultiTaskElasticNetCVRegressor, MultiTaskElasticNetRegressor, MultiTaskLassoCVRegressor, MultiTaskLassoRegressor, MultinomialNBClassifier, OPTICS, OrthogonalMatchingPursuitCVRegressor, OrthogonalMatchingPursuitRegressor, PassiveAggressiveClassifier, PassiveAggressiveRegressor, PerceptronClassifier, ProbabilisticSGDClassifier, RANSACRegressor, RandomForestClassifier, RandomForestRegressor, RidgeCVClassifier, RidgeCVRegressor, RidgeClassifier, RidgeRegressor, SGDClassifier, SGDRegressor, SVMClassifier, SVMLClassifier, SVMLRegressor, SVMNuClassifier, SVMNuRegressor, SVMRegressor, SpectralClustering, TheilSenRegressor | high | †
-[TSVD.jl](https://github.com/JuliaLinearAlgebra/TSVD.jl) | TSVDTransformer | high | 
-[XGBoost.jl](https://github.com/dmlc/XGBoost.jl) | XGBoostRegressor, XGBoostClassifier, XGBoostCount | high |
+| Package | Interface Pkg | Models | Maturity | Note
+| ------- | ------------- | ------ | -------- | ----
+[BetaML.jl](https://github.com/sylvaticus/BetaML.jl) | - | BetaMLGMMImputer, BetaMLGMMRegressor, BetaMLGenericImputer, BetaMLMeanImputer, BetaMLRFImputer, DecisionTreeClassifier, DecisionTreeRegressor, GMMClusterer, KMeans, KMedoids, KernelPerceptronClassifier, MissingImputator, PegasosClassifier, PerceptronClassifier, RandomForestClassifier, RandomForestRegressor | medium |
+[Clustering.jl](https://github.com/JuliaStats/Clustering.jl) | [MLJClusteringInterface.jl](https://github.com/JuliaAI/MLJClusteringInterface.jl) | KMeans, KMedoids | high | †
+[DecisionTree.jl](https://github.com/bensadeghi/DecisionTree.jl) | [MLJDecisionTreeInterface.jl](https://github.com/JuliaAI/MLJDecisionTreeInterface.jl) | DecisionTreeClassifier, DecisionTreeRegressor, AdaBoostStumpClassifier, RandomForestClassifier, RandomForestRegressor | high | 
+[EvoTrees.jl](https://github.com/Evovest/EvoTrees.jl) | - | EvoTreeRegressor, EvoTreeClassifier, EvoTreeCount, EvoTreeGaussian | medium | gradient boosting models
+[GLM.jl](https://github.com/JuliaStats/GLM.jl) | [MLJGLMInterface.jl](https://github.com/JuliaAI/MLJGLMInterface.jl) | LinearRegressor, LinearBinaryClassifier, LinearCountRegressor | medium | †
+[LIBSVM.jl](https://github.com/mpastell/LIBSVM.jl) | [MLJLIBSVMInterface.jl](https://github.com/JuliaAI/MLJLIBSVMInterface.jl) | LinearSVC, SVC, NuSVC, NuSVR, EpsilonSVR, OneClassSVM | high | also via ScikitLearn.jl
+[LightGBM.jl](https://github.com/IQVIA-ML/LightGBM.jl) | - | LGBMClassifier, LGBMRegressor | high | 
+[Flux.jl](https://github.com/FluxML/Flux.jl) | [MLJFlux.jl](https://github.com/FluxML/MLJFlux.jl) | NeuralNetworkRegressor, NeuralNetworkClassifier, MultitargetNeuralNetworkRegressor, ImageClassifier | low |
+[MLJLinearModels.jl](https://github.com/JuliaAI/MLJLinearModels.jl) | - | LinearRegressor, RidgeRegressor, LassoRegressor, ElasticNetRegressor, QuantileRegressor, HuberRegressor, RobustRegressor, LADRegressor, LogisticClassifier, MultinomialClassifier | medium |
+[MLJModels.jl](https://github.com/JuliaAI/MLJModels.jl) (built-in) | - | StaticTransformer, FeatureSelector, FillImputer, UnivariateStandardizer, Standardizer, UnivariateBoxCoxTransformer, OneHotEncoder, ContinuousEncoder, ConstantRegressor, ConstantClassifier, BinaryThreshholdPredictor | medium |
+[MLJText.jl](https://github.com/JuliaAI/MLJText.jl) | - | TfidfTransformer, BM25Transformer, CountTransformer | low |
+[MultivariateStats.jl](https://github.com/JuliaStats/MultivariateStats.jl) | [MLJMultivariateStatsInterface.jl](https://github.com/JuliaAI/MLJMultivariateStatsInterface.jl) | LinearRegressor, MultitargetLinearRegressor, RidgeRegressor, MultitargetRidgeRegressor, PCA, KernelPCA, ICA, LDA, BayesianLDA, SubspaceLDA, BayesianSubspaceLDA, FactorAnalysis, PPCA | high | 
+[NaiveBayes.jl](https://github.com/dfdx/NaiveBayes.jl) | [MLJNaiveBayesInterface.jl](https://github.com/JuliaAI/MLJNaiveBayesInterface.jl) | GaussianNBClassifier, MultinomialNBClassifier, HybridNBClassifier | low |
+[NearestNeighborModels.jl](https://github.com/JuliaAI/NearestNeighborModels.jl) | - | KNNClassifier, KNNRegressor, MultitargetKNNClassifier, MultitargetKNNRegressor | high |
+[OneRule.jl](https://github.com/roland-KA/OneRule.jl) | - | OneRuleClassifier | experimental |
+[OutlierDetectionNeighbors.jl](https://github.com/OutlierDetectionJL/OutlierDetectionNeighbors.jl) | - | ABODDetector, COFDetector, DNNDetector, KNNDetector, LOFDetector | medium | 
+[OutlierDetectionNetworks.jl](https://github.com/OutlierDetectionJL/OutlierDetectionNetworks.jl) | - | AEDetector, DSADDetector, ESADDetector | medium | 
+[OutlierDetectionPython.jl](https://github.com/OutlierDetectionJL/OutlierDetectionPython.jl) | - | ABODDetector, CBLOFDetector, COFDetector, COPODDetector, HBOSDetector, IForestDetector, KNNDetector, LMDDDetector, LOCIDetector, LODADetector, LOFDetector, MCDDetector, OCSVMDetector, PCADetector, RODDetector, SODDetector, SOSDetector | high | 
+[ParallelKMeans.jl](https://github.com/PyDataBlog/ParallelKMeans.jl) | - | KMeans | experimental |
+[PartialLeastSquaresRegressor.jl](https://github.com/lalvim/PartialLeastSquaresRegressor.jl) | - | PLSRegressor, KPLSRegressor | experimental |
+[ScikitLearn.jl](https://github.com/cstjean/ScikitLearn.jl) | [MLJScikitLearnInterface.jl](https://github.com/JuliaAI/MLJScikitLearnInterface.jl) | ARDRegressor, AdaBoostClassifier, AdaBoostRegressor, AffinityPropagation, AgglomerativeClustering, BaggingClassifier, BaggingRegressor, BayesianLDA, BayesianQDA, BayesianRidgeRegressor, BernoulliNBClassifier, Birch, ComplementNBClassifier, DBSCAN, DummyClassifier, DummyRegressor, ElasticNetCVRegressor, ElasticNetRegressor, ExtraTreesClassifier, ExtraTreesRegressor, FeatureAgglomeration, GaussianNBClassifier, GaussianProcessClassifier, GaussianProcessRegressor, GradientBoostingClassifier, GradientBoostingRegressor, HuberRegressor, KMeans, KNeighborsClassifier, KNeighborsRegressor, LarsCVRegressor, LarsRegressor, LassoCVRegressor, LassoLarsCVRegressor, LassoLarsICRegressor, LassoLarsRegressor, LassoRegressor, LinearRegressor, LogisticCVClassifier, LogisticClassifier, MeanShift, MiniBatchKMeans, MultiTaskElasticNetCVRegressor, MultiTaskElasticNetRegressor, MultiTaskLassoCVRegressor, MultiTaskLassoRegressor, MultinomialNBClassifier, OPTICS, OrthogonalMatchingPursuitCVRegressor, OrthogonalMatchingPursuitRegressor, PassiveAggressiveClassifier, PassiveAggressiveRegressor, PerceptronClassifier, ProbabilisticSGDClassifier, RANSACRegressor, RandomForestClassifier, RandomForestRegressor, RidgeCVClassifier, RidgeCVRegressor, RidgeClassifier, RidgeRegressor, SGDClassifier, SGDRegressor, SVMClassifier, SVMLClassifier, SVMLRegressor, SVMNuClassifier, SVMNuRegressor, SVMRegressor, SpectralClustering, TheilSenRegressor | high | †
+[TSVD.jl](https://github.com/JuliaLinearAlgebra/TSVD.jl) | [MLJTSVDInterface.jl](https://github.com/JuliaAI/MLJTSVDInterface.jl) | TSVDTransformer | high | 
+[XGBoost.jl](https://github.com/dmlc/XGBoost.jl) | [MLJXGBoostInterface.jl](https://github.com/JuliaAI/MLJXGBoostInterface.jl) | XGBoostRegressor, XGBoostClassifier, XGBoostCount | high |
 
 **Note** (†): Some models are missing and assistance is welcome to
 complete the interface. Post a message on the Julia #mlj Slack channel