Add benchmarking dataset with labelled anomalies for scoring performance of detector algorithms
Open
help wanted
- Dominant language
- Python
- Stars
- 191
- Forks
- 19
- PR merge metrics
- No merged PRs in 30d
Description
Do you know about any (open source) datasets at DHI that has labelled anomalies that we can use for testing? @ecomodeller @laurafroelich @akfDHI
Contributor guide
No contributing guide indexed for this repository
Research direction
Start by reviewing the repository's existing dataset and detector evaluation entry points, then investigate whether DHI has an open-source dataset with labelled anomalies. Clarify the dataset format, anomaly labels, licensing, and scoring procedure before implementation. Done means an agreed benchmark dataset is available and can be used to compare detector performance reproducibly.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100