Wolfram Language Paclet Repository
Community-contributed installable additions to the Wolfram Language
AntonAntonov`ClassifierEnsembles`
EnsembleClassifier  |
|
| | ||||
Examples
(2)
Basic Examples
(1)
Get training data:
In[1]:=
data=ExampleData[{"MachineLearning","Titanic"},"TrainingData"];data=((Flatten@*List)@@@data)〚All,{1,2,3,-1}〛;trainingData=DeleteCases[data,{___,_Missing,___}];
Get testing data:
In[2]:=
data=ExampleData[{"MachineLearning","Titanic"},"TestData"];data=((Flatten@*List)@@@data)〚All,{1,2,3,-1}〛;testData=DeleteCases[data,{___,_Missing,___}];
Make an ensemble classifier using three different methods:
In[3]:=
aCLs=
[{"NearestNeighbors","RandomForest","LogisticRegression"},Thread[trainingData〚All,1;;-2〛trainingData〚All,-1〛]];aCLs//Length
 | EnsembleClassifier |
Out[3]=
3
Display the elements of the ensemble classifier:
In[4]:=
ResourceFunction["GridTableForm"][List@@@Normal[aCLs],TableHeadings{"Classifier name","Classifier"}]
Out[4]=
# | Classifier name | Classifier | |||||
1 | NearestNeighbors | ClassifierFunction
| |||||
2 | RandomForest | ClassifierFunction
| |||||
3 | LogisticRegression | ClassifierFunction
|
Compute classifier measurements:
In[5]:=
measures={"Accuracy","Precision","Recall"};
[aCLs,Thread[testData〚All,1;;-2〛testData〚All,-1〛],measures]//AssociationThread[measures,#]&
 | EnsembleClassifierMeasurements |
Out[5]=
Accuracy0.812102,Precisiondied0.812207,survived0.811881,Recalldied0.901042,survived0.672131
Generalizations & Extensions
(1)
 |
|
""