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本章介绍了使用机器学习进行异常检测的方法，包括KNN、LOF、iForest、OCSVM和COPOD，并通过PyOD库进行实现。讨论了不同方法如何捕捉异常并对比真实标签，以纽约出租车数据集为例。此外，还展示了如何使用PyCaret快速评估多个异常检测模型。
In ts8_Outlier Detection_plotly_sns_text annot_modified z-score_hist_Tukey box_cdf_resample freq_Quanti_LIQING LIN的博客-优快云博客, Outlier Detection Using Statistical Methods, you explored parametric and non-parametric statistical techniques to spot potential outliers. The methods were simple, interpretable, and yet quite effective.
Outlier detection is not straightforward, mainly due to the ambiguity/ˌæmbɪˈɡjuːəti; ˌæmbɪˈɡjuːɪti/不明确, 歧义 surrounding the definition of what an outlier is specific t
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