add missing model descriptors

oops

docs/ModelDescriptors.toml

@@ -66,8 +66,8 @@ EvoSplineRegressor_EvoLinear = ["regression", "ensemble_models", "iterative_mode
 ExtraTreesClassifier_MLJScikitLearnInterface = ["classification", "iterative_models"]
 ExtraTreesRegressor_MLJScikitLearnInterface = ["regression", "iterative_models"]
 FactorAnalysis_MultivariateStats = ["dimension_reduction", ]
-FeatureAgglomeration_MLJScikitLearnInterface = ["clustering", "static_models"]
-FeatureSelector_MLJModels = ["dimension_reduction", ]
+FeatureAgglomeration_MLJScikitLearnInterface = ["clustering", "static_models", "feature_engineering"]
+FeatureSelector_FeatureSelection = ["dimension_reduction", "feature_engineering"]
 FillImputer_MLJModels = ["missing_value_imputation", ]
 GaussianMixtureClusterer_BetaML = ["clustering", "distribution_fitter"]
 GaussianMixtureImputer_BetaML = ["missing_value_imputation", "distribution_fitter"]
@@ -91,7 +91,7 @@ ICA_MultivariateStats = ["encoders"]
 IForestDetector_OutlierDetectionPython = ["outlier_detection"]
 ImageClassifier_MLJFlux = ["classification", "image_processing", "iterative_models"]
 INNEDetector_OutlierDetectionPython = ["outlier_detection"]
-InteractionTransformer_MLJModels = ["static_models"]
+InteractionTransformer_MLJModels = ["static_models", "feature_engineering"]
 IteratedModel_MLJIteration = ["iterative_models", "meta_algorithms"]
 KDEDetector_OutlierDetectionPython = ["outlier_detection"]
 KMeansClusterer_BetaML = ["clustering"]
@@ -195,6 +195,7 @@ RandomForestImputer_BetaML = ["missing_value_imputation", "ensemble_models", "it
 RandomForestRegressor_BetaML = ["regression", "ensemble_models", "iterative_models"]
 RandomForestRegressor_DecisionTree = ["regression", "ensemble_models", "iterative_models"]
 RandomForestRegressor_MLJScikitLearnInterface = ["regression", "ensemble_models", "iterative_models"]
+RecursiveFeatureElimination_FeatureSelection = ["dimension_reduction", "meta_algorithms", ["feature_engineering"]
 Resampler_MLJBase = ["meta_algorithms"]
 RidgeCVClassifier_MLJScikitLearnInterface = ["classification"]
 RidgeCVRegressor_MLJScikitLearnInterface = ["classification"]

test/integration.jl

@@ -55,7 +55,7 @@ FILTER_GIVEN_ISSUE = Dict(
         ],
     "https://github.com/JuliaAI/FeatureSelection.jl/issues/15" =>
         model -> model.package_name == "FeatureSelection" &&
-        model.name = "RecursiveFeatureElimination"
+        model.name == "RecursiveFeatureElimination"
 )