An Information-theoretic Approach to Unsupervised Feature Selection for High-Dimensional Data.
Shao-Lun HuangXiangxiang XuLizhong ZhengPublished in: CoRR (2019)
Keyphrases
- high dimensional data
- unsupervised feature selection
- dimensionality reduction
- low dimensional
- high dimensional
- feature selection
- nearest neighbor
- cluster structure
- high dimensionality
- subspace clustering
- data points
- original data
- data clustering
- data matrix
- data analysis
- similarity search
- dimension reduction
- data sets
- pattern recognition
- missing values
- data distribution
- low rank
- sparse representation
- manifold learning
- linear discriminant analysis
- unsupervised learning
- principal component analysis
- gene expression data
- feature extraction
- neural network
- euclidean distance
- data representation
- data mining methods
- data mining applications
- nonnegative matrix factorization
- real world