Merge pull request #1091 from alan-turing-institute/dev

Update documentation to reflect recent BetaML reorganisation

docs/ModelDescriptors.toml

@@ -7,7 +7,7 @@ AdaBoostRegressor_MLJScikitLearnInterface = ["regression"]
 AdaBoostStumpClassifier_DecisionTree = ["classification"]
 AffinityPropagation_MLJScikitLearnInterface = ["clustering"]
 AgglomerativeClustering_MLJScikitLearnInterface = ["clustering", "static_models"]
-AutoEncoderMLJ_BetaML = ["dimension_reduction"]
+AutoEncoder_BetaML = ["dimension_reduction"]
 BM25Transformer_MLJText = ["encoders", "text_analysis"]
 BaggingClassifier_MLJScikitLearnInterface = ["classification", "ensemble_models"]
 BaggingRegressor_MLJScikitLearnInterface = ["regression", "ensemble_models"]
@@ -90,11 +90,11 @@ ImageClassifier_MLJFlux = ["classification", "image_processing", "iterative_mode
 INNEDetector_OutlierDetectionPython = ["outlier_detection"]
 InteractionTransformer_MLJModels = ["static_models"]
 KDEDetector_OutlierDetectionPython = ["outlier_detection"]
-KMeans_BetaML = ["clustering"]
+KMeansClusterer_BetaML = ["clustering"]
 KMeans_Clustering = ["clustering", "dimension_reduction", ]
 KMeans_ParallelKMeans = ["clustering", "dimension_reduction", ]
 KMeans_MLJScikitLearnInterface = ["clustering", "dimension_reduction", ]
-KMedoids_BetaML = ["clustering"]
+KMedoidsClusterer_BetaML = ["clustering"]
 KMedoids_Clustering = ["clustering", "dimension_reduction", ]
 KNNClassifier_NearestNeighborModels = ["classification"]
 KNNDetector_OutlierDetectionNeighbors = ["outlier_detection"]
@@ -104,7 +104,7 @@ KNeighborsClassifier_MLJScikitLearnInterface = ["classification"]
 KNeighborsRegressor_MLJScikitLearnInterface = ["regression"]
 KPLSRegressor_PartialLeastSquaresRegressor = ["regression"]
 KernelPCA_MultivariateStats = ["dimension_reduction", ]
-KernelPerceptron_BetaML = ["classification"]
+KernelPerceptronClassifier_BetaML = ["classification"]
 LADRegressor_MLJLinearModels = ["regression"]
 LDA_MultivariateStats = ["classification", "dimension_reduction", ]
 LGBMClassifier_LightGBM = ["classification", "ensemble_models", "iterative_models"]
@@ -124,7 +124,6 @@ LassoRegressor_MLJLinearModels = ["regression"]
 LassoRegressor_MLJScikitLearnInterface = ["regression"]
 LinearBinaryClassifier_GLM = ["classification"]
 LinearCountRegressor_GLM = ["regression"]
-LinearPerceptron_BetaML = ["classification"]
 LinearRegressor_GLM = ["regression"]
 LinearRegressor_MLJLinearModels = ["regression"]
 LinearRegressor_MultivariateStats = ["regression"]
@@ -170,8 +169,9 @@ PLSRegressor_PartialLeastSquaresRegressor = ["regression"]
 PPCA_MultivariateStats = ["dimension_reduction"]
 PassiveAggressiveClassifier_MLJScikitLearnInterface = ["classification"]
 PassiveAggressiveRegressor_MLJScikitLearnInterface = ["regression"]
-Pegasos_BetaML = ["classification"]
-PerceptronClassifier_MLJScikitLearnInterface = ["classification"]
+PegasosClassifier_BetaML = ["classification"]
+PerceptronClassifier_BetaML = ["classification", "iterative_models"]
+PerceptronClassifier_MLJScikitLearnInterface = ["classification", "iterative_models"]
 ProbabilisticNuSVC_LIBSVM = ["classification"]
 ProbabilisticSGDClassifier_MLJScikitLearnInterface = ["classification"]
 ProbabilisticSVC_LIBSVM = ["classification"]

docs/src/controlling_iterative_models.md

@@ -103,6 +103,7 @@ control                                                        | description
 [`GL`](@ref EarlyStopping.GL)`(alpha=2.0)`                     | † Stop after the "generalization loss (GL)" exceeds `alpha`                             | yes
 [`PQ`](@ref EarlyStopping.PQ)`(alpha=0.75, k=5)`               | † Stop after "progress-modified GL" exceeds `alpha`                                     | yes
 [`Patience`](@ref EarlyStopping.Patience)`(n=5)`               | † Stop after `n` consecutive loss increases                                             | yes
+[`Warmup`](@ref EarlyStopping.Warmup)`(c; n=1)`                | Wait for `n` loss updates before checking criteria `c`                                  | no
 [`Info`](@ref IterationControl.Info)`(f=identity)`             | Log to `Info` the value of `f(mach)`, where `mach` is current machine                   | no
 [`Warn`](@ref IterationControl.Warn)`(predicate; f="")`        | Log to `Warn` the value of `f` or `f(mach)`, if `predicate(mach)` holds                 | no
 [`Error`](@ref IterationControl.Error)`(predicate; f="")`      | Log to `Error` the value of `f` or `f(mach)`, if `predicate(mach)` holds and then stop  | yes

docs/src/list_of_supported_models.md

@@ -30,7 +30,7 @@ independent assessment.
 
 | Package | Interface Pkg | Models | Maturity | Note
 | ------- | ------------- | ------ | -------- | ----
-[BetaML.jl](https://github.com/sylvaticus/BetaML.jl) | - | DecisionTreeClassifier, RandomForestClassifier, NeuralNetworkClassifier, LinearPerceptron, KernelPerceptron, Pegasos, DecisionTreeRegressor, RandomForestRegressor, NeuralNetworkRegressor, MultitargetNeuralNetworkRegressor, GaussianMixtureRegressor, MultitargetGaussianMixtureRegressor, KMeans, KMedoids, GaussianMixtureClusterer,  SimpleImputer,  GaussianMixtureImputer, RandomForestImputer, GeneralImputer | medium |
+[BetaML.jl](https://github.com/sylvaticus/BetaML.jl) | - | DecisionTreeClassifier, RandomForestClassifier, NeuralNetworkClassifier, PerceptronClassifier, KernelPerceptronClassifier, PegasosClassifier, DecisionTreeRegressor, RandomForestRegressor, NeuralNetworkRegressor, MultitargetNeuralNetworkRegressor, GaussianMixtureRegressor, MultitargetGaussianMixtureRegressor, KMeansClusterer, KMedoidsClusterer, GaussianMixtureClusterer,  SimpleImputer,  GaussianMixtureImputer, RandomForestImputer, GeneralImputer, AutoEncoder | medium |
 [CatBoost.jl](https://github.com/JuliaAI/CatBoost.jl) | - | CatBoostRegressor, CatBoostClassifier | high |
 [Clustering.jl](https://github.com/JuliaStats/Clustering.jl) | [MLJClusteringInterface.jl](https://github.com/JuliaAI/MLJClusteringInterface.jl) | KMeans, KMedoids, DBSCAN, HierarchicalClustering | high² |
 [DecisionTree.jl](https://github.com/bensadeghi/DecisionTree.jl) | [MLJDecisionTreeInterface.jl](https://github.com/JuliaAI/MLJDecisionTreeInterface.jl) | DecisionTreeClassifier, DecisionTreeRegressor, AdaBoostStumpClassifier, RandomForestClassifier, RandomForestRegressor | high |