A Robust Outlier Detection Method in High-Dimensional Data Based on Mutual Information and Principal Component Analysis.
Hanlin WangZhijian LiPublished in: ICIC (LNAI 1) (2024)
Keyphrases
- detection method
- high dimensional data
- dimensionality reduction
- mutual information
- principal component analysis
- low dimensional
- dimension reduction
- lower dimensional
- linear discriminant analysis
- detection algorithm
- nearest neighbor
- high dimensionality
- high dimensions
- face detection
- subspace clustering
- high dimensional
- data sets
- data points
- clustering high dimensional data
- manifold learning
- feature selection
- similarity search
- input space
- subspace learning
- low rank
- original data
- data distribution
- outlier detection
- high dimensional datasets
- missing values
- image registration
- feature extraction
- locally linear embedding
- principal components
- similarity measure
- random projections
- high dimensional spaces
- data analysis
- feature space
- discriminant analysis
- region detection
- sparse representation
- dimensionality reduction methods
- pattern recognition
- input data
- training set
- nonlinear dimensionality reduction
- face recognition