xuhongzuo/outlier-interpretation
(WWW'21) ATON - an Outlier Interpreation / Outlier explanation method
This project helps data analysts and researchers understand *why* a particular data point is flagged as unusual or anomalous, rather than just knowing that it *is* an outlier. You input a dataset containing identified outliers, and it outputs an explanation: the specific features or aspects that make each outlier stand out. This helps subject matter experts gain deeper insights into their data.
188 stars. No commits in the last 6 months.
Use this if you have identified outliers in your data and need to understand the specific characteristics or features that make them anomalous.
Not ideal if your primary need is to simply detect outliers without needing an explanation for their unusual behavior.
Stars
188
Forks
25
Language
Python
License
Apache-2.0
Category
Last pushed
Jul 17, 2022
Commits (30d)
0
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