A multi-view classification and feature selection method via sparse low-rank regression analysis.
Yao LuYing-Lian GaoPei-Yong LiJin-Xing LiuPublished in: Int. J. Data Min. Bioinform. (2020)
Keyphrases
- regression analysis
- multi view
- feature selection
- low rank
- rank minimization
- missing data
- support vector machine
- feature set
- multiple views
- support vector
- support vector machine svm
- machine learning
- similarity measure
- feature space
- semi supervised
- high dimensionality
- structure from motion
- pairwise
- clustering method
- unsupervised learning
- model selection
- high dimensional
- sparse representation
- training samples
- training set
- high order
- singular value decomposition
- matrix factorization
- decision trees
- bundle adjustment
- image processing
- denoising