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분류 학습기 앱

대화형 방식으로 분류 모델 훈련, 검증 및 조정

이진 문제 또는 다중클래스 문제에 대해 분류 모델을 훈련시키고 검증하는 다양한 알고리즘 중에서 선택할 수 있습니다. 여러 모델을 훈련시킨 후 검증 오차를 나란히 비교한 다음 최적의 모델을 선택합니다. 어떤 알고리즘을 사용할지 결정하는 데 도움이 필요하다면 분류 학습기 앱에서 분류 모델을 훈련시키기 항목을 참조하십시오.

분류 학습기지도 기계 학습(Supervised Machine Learning)을 사용하여 데이터를 분류하도록 모델 훈련시키기

도움말 항목

분류 워크플로

분류 학습기 앱에서 분류 모델을 훈련시키기

자동화된 훈련, 수동 훈련, 병렬 훈련 등 분류 모델을 훈련시키고 비교하고 향상시킬 수 있는 워크플로입니다.

Select Data and Validation for Classification Problem

Import data into Classification Learner from the workspace or files, find example data sets, and choose cross-validation or holdout validation options.

Choose Classifier Options

In Classification Learner, automatically train a selection of models, or compare and tune options in decision tree, discriminant analysis, logistic regression, naive Bayes, support vector machine, nearest neighbor, and ensemble models.

Feature Selection and Feature Transformation Using Classification Learner App

Identify useful predictors using plots, manually select features to include, and transform features using PCA in Classification Learner.

Assess Classifier Performance in Classification Learner

Compare model accuracy scores, visualize results by plotting class predictions, and check performance per class in the Confusion Matrix.

Export Plots in Classification Learner App

Export and customize plots created before and after training.

Export Classification Model to Predict New Data

After training in Classification Learner, export models to the workspace, generate MATLAB® code, or generate C code for prediction.

분류 예제

Train Decision Trees Using Classification Learner App

Create and compare classification trees, and export trained models to make predictions for new data.

Train Discriminant Analysis Classifiers Using Classification Learner App

Create and compare discriminant analysis classifiers, and export trained models to make predictions for new data.

Train Logistic Regression Classifiers Using Classification Learner App

Create and compare logistic regression classifiers, and export trained models to make predictions for new data.

Train Support Vector Machines Using Classification Learner App

Create and compare support vector machine (SVM) classifiers, and export trained models to make predictions for new data.

Train Nearest Neighbor Classifiers Using Classification Learner App

Create and compare nearest neighbor classifiers, and export trained models to make predictions for new data.

Train Ensemble Classifiers Using Classification Learner App

Create and compare ensemble classifiers, and export trained models to make predictions for new data.

Train Naive Bayes Classifiers Using Classification Learner App

Create and compare naive Bayes classifiers, and export trained models to make predictions for new data.

Code Generation and Classification Learner App

Train a classification model using the Classification Learner app, and generate C/C++ code for prediction.