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Ensembles de clasificación

Potenciación, bosque aleatorio, empaquetado, subespacio aleatorio y ensembles ECOC para aprendizaje multiclase

Un ensemble de clasificación es un modelo predictivo compuesto por una combinación ponderada de varios modelos de clasificación. En general, la combinación de varios modelos de clasificación aumenta la capacidad predictiva.

Para explorar ensembles de clasificación de forma interactiva, utilice la app Classification Learner. Para mayor flexibilidad, utilice fitcensemble en la interfaz de línea de comandos para potenciar o empaquetar árboles de clasificación o aumentar un bosque aleatorio [12]. Para obtener información sobre todos los ensembles compatibles, consulte Ensemble Algorithms. Para reducir un problema multiclase a un ensemble de problemas de clasificación binaria, entrene un modelo de códigos de salida de corrección de errores (ECOC, por sus siglas en inglés). Para obtener más detalles, consulte fitcecoc.

Para potenciar árboles de regresión mediante LSBoost o aumentar un bosque aleatorio de árboles de regresión[12], consulte Ensembles de regresión.

Apps

Classification LearnerEntrenar modelos para clasificar datos usando machine learning supervisado

Bloques

ClassificationEnsemble PredictClassify observations using ensemble of decision trees

Funciones

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templateDiscriminantDiscriminant analysis classifier template
templateECOCError-correcting output codes learner template
templateEnsembleEnsemble learning template
templateKNNk-nearest neighbor classifier template
templateLinearLinear classification learner template
templateNaiveBayesNaive Bayes classifier template
templateSVMSupport vector machine template
templateTreeCreate decision tree template

Crear un ensemble de clasificación

fitcensembleFit ensemble of learners for classification
compactCompact classification ensemble

Modificar un ensemble de clasificación

resumeResume training ensemble
removeLearnersRemove members of compact classification ensemble

Interpretar un ensemble de clasificación

limeLocal interpretable model-agnostic explanations (LIME)
partialDependenceCompute partial dependence
plotPartialDependenceCreate partial dependence plot (PDP) and individual conditional expectation (ICE) plots
predictorImportanceEstimates of predictor importance for classification ensemble of decision trees
shapleyShapley values

Ensemble de clasificación de validación cruzada

crossvalCross-validate ensemble
kfoldEdgeClassification edge for cross-validated classification model
kfoldLossClassification loss for cross-validated classification model
kfoldMarginClassification margins for cross-validated classification model
kfoldPredictClassify observations in cross-validated classification model
kfoldfunCross-validate function for classification

Medir el rendimiento

lossClassification error
resubLossClassification error by resubstitution
compareHoldoutCompare accuracies of two classification models using new data
edgeClassification edge
marginClassification margins
resubEdgeClassification edge by resubstitution
resubMarginClassification margins by resubstitution
testckfoldCompare accuracies of two classification models by repeated cross-validation

Clasificar observaciones

predictClassify observations using ensemble of classification models
resubPredictClassify observations in ensemble of classification models
oobPredictPredict out-of-bag response of ensemble

Recopilar propiedades de un ensemble de clasificación

gatherGather properties of Statistics and Machine Learning Toolbox object from GPU
TreeBagger
fitcensembleFit ensemble of learners for classification
predictPredict responses using ensemble of bagged decision trees
oobPredictEnsemble predictions for out-of-bag observations

Crear un modelo ECOC

fitcecocFit multiclass models for support vector machines or other classifiers
compactReduce size of multiclass error-correcting output codes (ECOC) model

Modificar un modelo ECOC

discardSupportVectorsDiscard support vectors of linear SVM binary learners in ECOC model

Interpretar un modelo ECOC

limeLocal interpretable model-agnostic explanations (LIME)
partialDependenceCompute partial dependence
plotPartialDependenceCreate partial dependence plot (PDP) and individual conditional expectation (ICE) plots
shapleyShapley values

ECOC de validación cruzada

crossvalCross-validate multiclass error-correcting output codes (ECOC) model
kfoldEdgeClassification edge for cross-validated ECOC model
kfoldLossClassification loss for cross-validated ECOC model
kfoldMarginClassification margins for cross-validated ECOC model
kfoldPredictClassify observations in cross-validated ECOC model
kfoldfunCross-validate function using cross-validated ECOC model

Medir el rendimiento

lossClassification loss for multiclass error-correcting output codes (ECOC) model
resubLossResubstitution classification loss for multiclass error-correcting output codes (ECOC) model
compareHoldoutCompare accuracies of two classification models using new data
edgeClassification edge for multiclass error-correcting output codes (ECOC) model
marginClassification margins for multiclass error-correcting output codes (ECOC) model
resubEdgeResubstitution classification edge for multiclass error-correcting output codes (ECOC) model
resubMarginResubstitution classification margins for multiclass error-correcting output codes (ECOC) model
testckfoldCompare accuracies of two classification models by repeated cross-validation

Clasificar observaciones

predictClassify observations using multiclass error-correcting output codes (ECOC) model
resubPredictClassify observations in multiclass error-correcting output codes (ECOC) model

Recopilar propiedades de un modelo ECOC

gatherGather properties of Statistics and Machine Learning Toolbox object from GPU

Clases

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ClassificationEnsembleEnsemble classifier
CompactClassificationEnsembleCompact classification ensemble class
ClassificationPartitionedEnsembleCross-validated classification ensemble
TreeBaggerEnsemble of bagged decision trees
CompactTreeBaggerCompact ensemble of bagged decision trees
ClassificationBaggedEnsembleClassification ensemble grown by resampling
ClassificationECOCMulticlass model for support vector machines (SVMs) and other classifiers
CompactClassificationECOCCompact multiclass model for support vector machines (SVMs) and other classifiers
ClassificationPartitionedECOCCross-validated multiclass ECOC model for support vector machines (SVMs) and other classifiers

Temas