Ratio sum formula for dimensionality reduction.
Ke LiangXiaojun YangYuxiong XuRong WangFeiping NiePublished in: Multim. Tools Appl. (2021)
Keyphrases
- dimensionality reduction
- low dimensional
- high dimensional data
- principal component analysis
- feature extraction
- high dimensional
- pattern recognition and machine learning
- data representation
- pattern recognition
- objective function
- preprocessing step
- input space
- manifold learning
- nonlinear dimensionality reduction
- structure preserving
- high dimensionality
- intrinsic dimensionality
- random projections
- linear dimensionality reduction
- linear discriminant analysis
- principal components
- standard deviation
- weighted sum
- square error
- feature selection
- kernel pca
- least squares
- data points
- singular value decomposition
- sparse representation
- dimensionality reduction methods
- nearest neighbor
- support vector
- image processing
- knowledge base
- data sets
- supervised dimensionality reduction