Unsupervised Feature Selection via Adaptive Feature Clustering for High-dimensional Data.
Hong JiaYubin WengPublished in: DSIT (2022)
Keyphrases
- high dimensional data
- unsupervised feature selection
- dimensionality reduction
- cluster structure
- subspace clustering
- data points
- nearest neighbor
- data clustering
- low dimensional
- high dimensionality
- feature selection
- clustering high dimensional data
- original data
- high dimensional
- similarity search
- data matrix
- missing values
- data sets
- high dimensional data sets
- data analysis
- manifold learning
- high dimensional datasets
- dimension reduction
- input data
- feature subset
- sparse representation
- low rank
- unsupervised learning
- linear discriminant analysis
- data representation
- gene expression data
- feature vectors
- pattern recognition
- clustering algorithm
- clustering method
- training set
- negative matrix factorization
- computer vision
- principal component analysis
- real world
- neural network