yzhao062/pyod

ECOD and COPOD `explain_outlier` on new data?

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#408 创建于 2022年5月17日

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 (2 评论) (0 反应) (0 负责人)Python (7,762 star) (1,308 fork)batch import
enhancementhelp wanted

描述

Hi there,

Really like the python package, have been using it for a while. I was wondering if it was possible for explain_outlier method in ECOD and COPOD to be adapted as to accept new data not used during training?

Or at least to return the scores per feature given a event, as I don't need the graphic just to interpret why something was flagged as anomalous/has such a high anomaly score.

Cheers

贡献者指南

技术栈
python
领域
machine learningdata
议题类型
feature
难度面向新贡献者的预计实现难度，1 表示很小改动，5 表示专家级工作。
3
预计时间有经验贡献者完成调查、实现、测试并准备 pull request 的粗略时间范围。
1-2 days
活动状态议题当前的可参与程度：新鲜、活跃、陈旧、阻塞或等待维护者输入。
stale
清晰度议题是否清楚说明期望改动、验收标准和下一步。
clear
前置要求
Pythonpyod libraryanomaly detection basics
新手友好度1-100 的估计分数，表示该议题对首次贡献者的友好程度。
40
研究方向
Examine the current implementation of explain outlier in ECOD and COPOD (likely in pyod/models/ecod.py and pyod/models/copod.py) to understand how it computes per feature scores using training data. Then design modifications to accept new data at inference time, possibly by caching necessary statistics from training. Also consider separating the score computation from the plotting function to allow users to retrieve scores programmatically. Check existing documentation and ensure backward compatibility.