A hybrid dimensionality reduction method for outlier detection in high-dimensional data.
Guanglei MengBiao WangYanming WuMingzhe ZhouTiankuo MengPublished in: Int. J. Mach. Learn. Cybern. (2023)
Keyphrases
- high dimensional data
- outlier detection
- dimensionality reduction
- dimensionality reduction methods
- high dimensional datasets
- high dimensional data analysis
- high dimensional
- low dimensional
- high dimensionality
- data sets
- principal component analysis
- dimension reduction
- linear discriminant analysis
- detection algorithm
- knowledge discovery
- pattern recognition
- input space
- similarity search
- original data
- discriminant analysis
- data streams
- manifold learning
- data points
- feature extraction
- preprocessing step
- sparse representation
- data distribution
- supervised dimensionality reduction
- random projections
- data mining
- locally linear embedding
- feature selection
- principal components analysis
- lower dimensional
- euclidean distance
- feature space
- singular value decomposition
- nearest neighbor
- dimensional data
- high dimensional spaces
- variable selection
- multimodal data
- data analysis
- computer vision
- input data
- face recognition
- support vector
- knn
- distance measure
- unsupervised learning