A General Framework for Dimensionality Reduction of K-Means Clustering.
Tong WuYanni XiaoMuhan GuoFeiping NiePublished in: J. Classif. (2020)
Keyphrases
- dimensionality reduction
- high dimensional
- low dimensional
- high dimensional data
- pattern recognition and machine learning
- data representation
- principal component analysis
- principal components
- high dimensionality
- linear dimensionality reduction
- manifold learning
- k means
- feature selection
- input space
- linear discriminant analysis
- structure preserving
- feature space
- feature extraction
- random projections
- singular value decomposition
- data points
- spectral clustering
- pattern recognition
- metric learning
- intrinsic dimensionality
- image processing
- dimensionality reduction methods
- preprocessing step
- sparse representation
- linear projection
- partitioned data
- multidimensional scaling
- nonlinear dimensionality reduction
- pattern classification
- euclidean distance
- clustering algorithm
- supervised dimensionality reduction