Main Content


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.

분류 학습기머신러닝 지도 학습을 사용하여 데이터를 분류하도록 모델 훈련시키기


모두 확장

fitcdiscrFit discriminant analysis classifier
makecdiscrConstruct discriminant analysis classifier from parameters
compactCompact discriminant analysis classifier
cvshrinkCross-validate regularization of linear discriminant
partialDependenceCompute partial dependence
plotPartialDependenceCreate partial dependence plot (PDP) and individual conditional expectation (ICE) plots
crossvalCross-validated discriminant analysis classifier
kfoldEdgeClassification edge for observations not used for training
kfoldLossClassification loss for observations not used for training
kfoldfunCross validate function
kfoldMarginClassification margins for observations not used for training
kfoldPredictPredict response for observations not used for training
lossClassification error
resubLossClassification error by resubstitution
logpLog unconditional probability density for discriminant analysis classifier
mahalMahalanobis distance to class means
nLinearCoeffsNumber of nonzero linear coefficients
compareHoldoutCompare accuracies of two classification models using new data
edgeClassification edge
marginClassification margins
resubEdgeClassification edge by resubstitution
resubMarginClassification margins by resubstitution
predictPredict labels using discriminant analysis classification model
resubPredictPredict resubstitution labels of discriminant analysis classification model
classifyDiscriminant analysis


ClassificationDiscriminantDiscriminant analysis classification
CompactClassificationDiscriminantCompact discriminant analysis class
ClassificationPartitionedModelCross-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.