A Light Causal Feature Selection Approach to High-Dimensional Data.
Zhaolong LingYing LiYiwen ZhangKui YuPeng ZhouBo LiXindong WuPublished in: IEEE Trans. Knowl. Data Eng. (2023)
Keyphrases
- high dimensional data
- feature selection
- dimensionality reduction
- high dimensionality
- dimension reduction
- high dimensional
- low dimensional
- nearest neighbor
- gene expression data
- high dimensions
- data analysis
- markov blanket
- similarity search
- original data
- feature space
- data sets
- subspace clustering
- linear discriminant analysis
- high dimensional datasets
- sparse representation
- input space
- subspace learning
- data points
- variable selection
- lower dimensional
- manifold learning
- missing values
- selected features
- small sample size
- high dimensional spaces
- clustering high dimensional data
- pattern recognition
- data distribution
- machine learning
- knn
- principal component analysis
- feature extraction
- nonlinear dimensionality reduction
- dimensional data
- support vector machine
- feature set
- input data
- text data
- text classification
- text categorization
- euclidean distance
- feature selection algorithms
- preprocessing step
- locally linear embedding
- support vector
- multi task
- image processing