Sparse Principal Component Analysis Based on Least Trimmed Squares
- Resource Type
- Authors
- Stefan Van Aelst; Yixin Wang
- Source
- Technometrics. 62:473-485
- Subject
- Statistics and Probability
business.industry
Applied Mathematics
Dimensionality reduction
Sparse PCA
Least trimmed squares
Pattern recognition
ComputingMethodologies_PATTERNRECOGNITION
Robustness (computer science)
Computer Science::Computer Vision and Pattern Recognition
Modeling and Simulation
Principal component analysis
Artificial intelligence
business
Mathematics
- Language
- ISSN
- 1537-2723
0040-1706
Sparse principal component analysis (PCA) is used to obtain stable and interpretable principal components (PCs) from high-dimensional data. A robust sparse PCA method is proposed to handle potentia...