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Regression Learner App

以交互方式训练、验证和调整回归模型

可以选择各种算法来训练和验证回归模型。训练多个模型后,可以横向比较它们的验证误差,然后选择最佳模型。要帮助您确定使用哪种算法,请参阅Train Regression Models in Regression Learner App

此流程图显示在 Regression Learner 中训练回归模型的常见工作流。

App

Regression LearnerTrain regression models to predict data using supervised machine learning

主题

常见工作流

Train Regression Models in Regression Learner App

Workflow for training, comparing and improving regression models, including automated, manual, and parallel training.

Select Data and Validation for Regression Problem

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

Choose Regression Model Options

In Regression Learner, automatically train a selection of models, or compare and tune options of linear regression models, regression trees, support vector machines, Gaussian process regression models, and ensembles of regression trees.

Assess Model Performance in Regression Learner

Compare model statistics and visualize results.

Export Regression Model to Predict New Data

After training in Regression Learner, export models to the workspace or generate MATLAB® code.

Train Regression Trees Using Regression Learner App

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

自定义工作流

Feature Selection and Feature Transformation Using Regression Learner App

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

Hyperparameter Optimization in Regression Learner App

Automatically tune hyperparameters of regression models by using hyperparameter optimization.

Train Regression Model Using Hyperparameter Optimization in Regression Learner App

Train a regression ensemble model with optimized hyperparameters.

Export Plots in Regression Learner App

Export and customize plots created before and after training.