您应该使用输出 cross_validate 的值以获取拟合模型的参数。原因是 cross_validate 会克隆管道。因此，在馈给 cross_validate 之后，您将找不到给定的管道变量是否适合。

You should use the output of cross_validate to get the parameters of the fitted model. The reason is that cross_validate would clone the pipeline. Hence you would not find given pipeline variable be fitted after been fed to cross_validate.

output 是字典，其中以 estimator 作为键之一，其值为a k_fold 个已拟合管道对象的数量。

output is dictionary, which has estimator as one of the keys, whose value is a k_fold number of fitted pipeline objects.

来自 文档 ：

return_estimator：布尔值，默认为False

return_estimator : boolean, default False

是否返回每个分割拟合的估计量。

Whether to return the estimators fitted on each split.

尝试一下！

>>> fitted_svc = output['estimator'][0].named_steps['svm'] # choosing the first fold comb
>>> fitted_svc.coef_

array([[1.05826838, 0.41630046]])