Writing example notebooks for MLJ registered models

If you are interested in writing a notebook to demonstrate the use of a specific model, then:

• Check out the existing examples in examples/ and any MLJ issues labelled "tutorial" to avoid duplication

• Open an issue on MLJ (eg, "Add tutorial for SVMClassifier") to stake your "claim"

• Label the issue "tutorial"

Each tutorial will live in a separate subdirectory of examples/ and will ideally include the relevant Project.toml file and Manifest.toml file along with the .jl script or notebook. In that case, to ensure the matching environment is loaded by the script, you can include these lines in the header:

# load local environment:
using Pkg
Pkg.activate(@__DIR__)
Pkg.instantiate()

To finish, make a pull request to have you example merged.

To obtain a list of models in MLJ, just use models(). Here a expanded, lightly edited version of the current output (package names removed):

 "RidgeRegressor"                              
 "PCA"                                         
 "Standardizer"                                
 "OneHotEncoder"                               
 "KNNRegressor"                                
 "UnivariateBoxCoxTransformer"                 
 "FeatureSelector"                             
 "UnivariateStandardizer"                      
 "DecisionTreeRegressor"                       
 "DecisionTreeClassifier"                      
 "SVMLRegressor"                               
 "SVMNuClassifier"                             
 "ElasticNet"                                  
 "ElasticNetCV"                                
 "SVMRegressor"                                
 "SVMNuRegressor"                              
 "SVMClassifier"                               
 "SVMLClassifier"                              
 "EpsilonSVR"                                  
 "LinearSVC"                                   
 "NuSVR"                                       
 "NuSVC"                                       
 "SVC"                                         
 "OneClassSVM"                                 
 "KMeans"                                      
 "KMedoids"                                    
 "OLSRegressor"                                
 "GLMCountRegressor"                           
 "GaussianNBClassifier"                        
 "MultinomialNBClassifier"                     
 "XGBoostCount"                                
 "XGBoostRegressor"                            
 "XGBoostClassifier"