A geometric framework for outlier detection in high-dimensional data.
Moritz HerrmannFlorian PfistererFabian ScheiplPublished in: WIREs Data. Mining. Knowl. Discov. (2023)
Keyphrases
- high dimensional data
- outlier detection
- high dimensional datasets
- high dimensional
- nearest neighbor
- dimensionality reduction
- high dimensionality
- low dimensional
- subspace clustering
- fraud detection
- similarity search
- knowledge discovery
- data analysis
- data streams
- clustering high dimensional data
- input space
- neural network
- manifold learning
- data sets
- high dimensional spaces
- density ratio estimation
- density estimation
- detection algorithm
- pattern recognition
- concept drift
- spatial outliers
- databases