scikit-learn - SKLearn中isolation_forest中的决策函数和score_samples有什么区别

Question

我已阅读决策函数和 score_samples 的文档 here , 但无法弄清楚这两种方法之间的区别是什么以及我应该将哪种方法用于异常值检测算法。

如有任何帮助，我们将不胜感激。

Answer 1

请参阅属性 offset_ 的文档:

Offset used to define the decision function from the raw scores. We have the relation: decision_function = score_samples - offset_. offset_ is defined as follows. When the contamination parameter is set to “auto”, the offset is equal to -0.5 as the scores of inliers are close to 0 and the scores of outliers are close to -1. When a contamination parameter different than “auto” is provided, the offset is defined in such a way we obtain the expected number of outliers (samples with decision function < 0) in training.