分类

Use fitcauto to automatically try a selection of classification model types with different hyperparameter values, given training predictor and response data.

Build multiple classification models, optimize their hyperparameters, and select the model that performs the best on a test data set.

Build multiple machine learning models for a given training data set, and then combine the models using a technique called stacking to improve the accuracy on a test data set compared to the accuracy of the individual models.

此示例说明如何使用判别分析、朴素贝叶斯分类器和决策树进行分类。

Build an automated credit rating tool.