판별분석

정규화된 선형 및 2차 판별분석

대화형 방식으로 판별분석 모델을 훈련시키려면 분류 학습기 앱을 사용하십시오. 명령줄 인터페이스에서 fitcdiscr을 사용하여 판별분석 모델을 훈련시키면 유연성을 높일 수 있습니다. 훈련 후에는 모델과 예측 변수 데이터를 predict에 전달하여 레이블을 예측하거나 사후 확률을 추정합니다.

앱

분류 학습기

머신러닝 지도 학습을 사용하여 데이터를 분류하도록 모델 훈련시키기

함수

모두 확장

판별분석 모델 만들기

`fitcdiscr`	Fit discriminant analysis classifier
`makecdiscr`	Construct discriminant analysis classifier from parameters
`compact`	Compact discriminant analysis classifier

판별분석 모델 개선하기

cvshrink Cross-validate regularization of linear discriminant

판별분석 모델 해석하기

`lime`	Local interpretable model-agnostic explanations (LIME)
`partialDependence`	Compute partial dependence
`plotPartialDependence`	Create partial dependence plot (PDP) and individual conditional expectation (ICE) plots
`shapley`	Shapley values

교차 검증하기

`crossval`	Cross-validated discriminant analysis classifier
`kfoldEdge`	Classification edge for cross-validated classification model
`kfoldLoss`	Classification loss for cross-validated classification model
`kfoldfun`	Cross-validate function for classification
`kfoldMargin`	Classification margins for cross-validated classification model
`kfoldPredict`	Classify observations in cross-validated classification model

성능 측정하기

`loss`	Classification error
`resubLoss`	Classification error by resubstitution
`logp`	Log unconditional probability density for discriminant analysis classifier
`mahal`	Mahalanobis distance to class means of discriminant analysis classifier
`nLinearCoeffs`	Number of nonzero linear coefficients
`compareHoldout`	Compare accuracies of two classification models using new data
`edge`	Classification edge
`margin`	Classification margins
`resubEdge`	Classification edge by resubstitution
`resubMargin`	Classification margins by resubstitution
`testckfold`	Compare accuracies of two classification models by repeated cross-validation

관측값 분류하기

`predict`	Predict labels using discriminant analysis classification model
`resubPredict`	Predict resubstitution labels of discriminant analysis classification model
`classify`	Classify observations using discriminant analysis

클래스

`ClassificationDiscriminant`	Discriminant analysis classification
`CompactClassificationDiscriminant`	Compact discriminant analysis class
`ClassificationPartitionedModel`	Cross-validated classification model

도움말 항목

Train Discriminant Analysis Classifiers Using Classification Learner App
Create and compare discriminant analysis classifiers, and export trained models to make predictions for new data.
지도 학습 워크플로와 알고리즘
지도 학습의 단계와 비모수적 분류 및 회귀 함수의 특성을 알아봅니다.
Parametric Classification
Categorical response data
판별분석 분류
판별분석 알고리즘 및 판별분석 모델을 데이터에 피팅하는 방법을 알아봅니다.
Creating Discriminant Analysis Model
Understand the algorithm used to construct discriminant analysis classifiers.
Create and Visualize Discriminant Analysis Classifier
Perform linear and quadratic classification of Fisher iris data.
Improving Discriminant Analysis Models
Examine and improve discriminant analysis model performance.
Regularize Discriminant Analysis Classifier
Make a more robust and simpler model by removing predictors without compromising the predictive power of the model.
Examine the Gaussian Mixture Assumption
Discriminant analysis assumes that the data comes from a Gaussian mixture model. Understand how to examine this assumption.
Prediction Using Discriminant Analysis Models
Understand how predict classifies observations using a discriminant analysis model.
Visualize Decision Surfaces of Different Classifiers
This example shows how to visualize the decision surface for different classification algorithms.