Merge pull request #1033 from alan-turing-institute/sirus_and_stable

add sirus.jl and symbolicregression.jl models to model browser

docs/ModelDescriptors.toml

@@ -141,6 +141,7 @@ MultitargetLinearRegressor_MultivariateStats = ["regression"]
 MultitargetNeuralNetworkRegressor_BetaML = ["regression"]
 MultitargetNeuralNetworkRegressor_MLJFlux = ["regression", "iterative_models"]
 MultitargetRidgeRegressor_MultivariateStats = ["regression"]
+MultitargetSRRegressor_SymbolicRegression = ["regression"]
 NeuralNetworkClassifier_BetaML = ["classification"]
 NeuralNetworkClassifier_MLJFlux = ["classification", "iterative_models"]
 NeuralNetworkRegressor_BetaML = ["regression"]
@@ -187,6 +188,11 @@ SGDClassifier_MLJScikitLearnInterface = ["classification"]
 SGDRegressor_MLJScikitLearnInterface = ["regression"]
 SODDetector_OutlierDetectionPython = ["outlier_detection", "outlier_detection"]
 SOSDetector_OutlierDetectionPython = ["outlier_detection"]
+SRRegressor_SymbolicRegression = ["regression"]
+StableForestClassifier_SIRUS = ["classification"]
+StableForestRegressor_SIRUS = ["regression"]
+StableRulesClassifier_SIRUS = ["classification"]
+StableRulesRegressor_SIRUS = ["regression"]
 SVC_LIBSVM = ["classification"]
 SVMClassifier_MLJScikitLearnInterface = ["classification"]
 SVMLinearClassifier_MLJScikitLearnInterface = ["classification"]

docs/src/list_of_supported_models.md

@@ -50,6 +50,8 @@ independent assessment.
 [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 | high² |
+[SIRUS.jl](https://github.com/rikhuijzer/SIRUS.jl) | - | StableForestClassifier, StableForestRegressor, StableRulesClassifier, StableRulesRegressor | low |
+[SymbolicRegression.jl](https://github.com/MilesCranmer/SymbolicRegression.jl) | - | MultitargetSRRegressor, SRRegressor | experimental |
 [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 |