Low-rank sparse feature selection with incomplete labels for Alzheimer's disease progression prediction.
Zhi ChenYongguo LiuYun ZhangRongjiang JinJing TaoLidian ChenPublished in: Comput. Biol. Medicine (2022)
Keyphrases
- low rank
- missing data
- low rank matrix
- rank minimization
- feature selection
- low rank matrices
- disease progression
- linear combination
- matrix factorization
- convex optimization
- regularized regression
- matrix completion
- singular value decomposition
- high dimensional data
- semi supervised
- missing values
- high order
- text classification
- feature space
- sparse matrix
- cross sectional
- text categorization
- machine learning
- computer aided diagnosis
- mutual information
- breast cancer
- sparse representation
- feature extraction
- clinical trials
- prostate cancer
- incomplete data
- pairwise
- high dimensionality
- blood vessels
- mathematical modeling
- data sets
- multi label
- pattern recognition
- support vector
- training data
- dimensionality reduction