detection of outliers (anomaly detection) using umap - robust dimension reduction
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- Python
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Description
Can I use umap for anomaly detection? Is the dimensionality reduction tolerant towards the outliers in the dataset or this totally screws up the results?
More generally I'm looking for generalization of robust PCA, but for nonlinear cases:
https://en.wikipedia.org/wiki/Robust_principal_component_analysis
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
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Research direction
No files, tests, or entry points are identified in the issue. Clarify whether the goal is documentation, an evaluation of UMAP's robustness, or a new robust nonlinear-reduction feature before implementation can be scoped.
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