python - sklearn.linear_model.SGDClassifier 中损失函数的精确定义

Question

我知道我可能会将损失函数更改为以下之一:

loss : str, 'hinge' or 'log' or 'modified_huber' The loss function to be used. Defaults to 'hinge'. The hinge loss is a margin loss used by standard linear SVM models. The 'log' loss is the loss of logistic regression models and can be used for probability estimation in binary classifiers. 'modified_huber' is another smooth loss that brings tolerance to outliers.

但是这个函数的定义是什么？
我知道 hinge 是 max(0, 1 - margin)。还有其他什么？

Answer 1

以下是所有这些函数的图表，取自 scikit-learn example gallery :

在当前dev version of the example ，损失在脚本中内联实现。