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分类是一种有监督的机器学习,在此过程中,算法“学习”如何对带标签的数据示例中的新观测值进行分类。要以交互方式研究分类模型,可以使用 Classification Learner App。为了获得更大的灵活性,您可以在命令行界面中将预测变量或特征数据以及对应的响应或标签传递给算法拟合函数。
要训练回归模型,例如逻辑回归、回归树、高斯过程回归和支持向量回归,请参阅回归。
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.
Build multiple classification models, optimize their hyperparameters, and select the model that performs the best on a test data set.
Use fitcauto to automatically try a selection of classification model types with different hyperparameter values, given training predictor and response data.
fitcauto
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