Calculating anomaly score for multivariate data set.
- Dominant language
- Python
- Stars
- 1.2k
- Forks
- 217
- PR merge metrics
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Description
I have been using Luminol to calculate anomaly scores for a univariate data sets(Timestamp & Value) and getting good results. Now, I want to move into multivariate data sets(Timestamp & Value 1 & Value 2 & .... & Value N) and detect a single anomaly score based upon all values. I finding hard on how to proceed with this problem statement. Is there a way I can apply Luminol to this problem or could you suggest me a way on how to proceed?
Thank you.
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Research direction
The issue does not name any files, tests, or entry points. Start by reviewing Luminol's existing anomaly-scoring interface and documentation to determine whether multivariate input is supported; done would require a documented, maintainer-approved approach for producing one score from multiple values.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100