주요 콘텐츠

분류 트리

다중클래스 학습을 위한 이진 결정 트리

분류 트리를 대화형 방식으로 성장시키려면 분류 학습기 앱을 사용하십시오. 더 유연한 접근 방법을 원한다면, 명령줄에서 fitctree를 사용하여 분류 트리를 성장시키십시오. 분류 트리를 성장시킨 후 트리와 새 예측 변수 데이터를 predict에 전달하여 레이블을 예측합니다.

분류 학습기머신러닝 지도 학습을 사용하여 데이터를 분류하도록 모델 훈련시키기

블록

ClassificationTree PredictClassify observations using decision tree classifier (R2021a 이후)

함수

모두 확장

fitctree다중클래스 분류를 위한 이진 결정 트리 피팅
compactReduce size of machine learning model
pruneProduce sequence of classification subtrees by pruning classification tree
cvlossClassification error by cross-validation for classification tree model
limeLocal interpretable model-agnostic explanations (LIME)
nodeVariableRangeRetrieve variable range of decision tree node
partialDependenceCompute partial dependence
permutationImportancePredictor importance by permutation (R2024a 이후)
plotPartialDependenceCreate partial dependence plot (PDP) and individual conditional expectation (ICE) plots
predictorImportanceEstimates of predictor importance for classification tree
shapleyShapley values (R2021a 이후)
surrogateAssociationMean predictive measure of association for surrogate splits in classification tree
viewView classification tree
crossvalCross-validate machine learning model
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
lossClassification loss for classification tree model
resubLossResubstitution classification loss for classification tree model
compareHoldoutCompare accuracies of two classification models using new data
edgeClassification edge for classification tree model
marginClassification margins for classification tree model
resubEdgeResubstitution classification edge for classification tree model
resubMarginResubstitution classification margins for classification tree model
testckfoldCompare accuracies of two classification models by repeated cross-validation
predictPredict labels using classification tree model
resubPredictClassify observations in classification tree by resubstitution
gatherGather properties of Statistics and Machine Learning Toolbox object from GPU

객체

ClassificationTreeBinary decision tree for multiclass classification
CompactClassificationTreeCompact classification tree
ClassificationPartitionedModelCross-validated classification model

도움말 항목