Dimensionality reduction to maximize prediction generalization capability.
Takuya IsomuraTaro ToyoizumiPublished in: CoRR (2020)
Keyphrases
- dimensionality reduction
- prediction accuracy
- prediction model
- feature extraction
- feature space
- principal component analysis
- data representation
- high dimensional data
- high dimensional
- nonlinear dimensionality reduction
- pattern recognition and machine learning
- linear discriminant analysis
- feature selection
- prediction algorithm
- machine learning
- dimensionality reduction methods
- linear dimensionality reduction
- kernel learning
- random projections
- prediction error
- semi supervised dimensionality reduction
- manifold learning
- low dimensional
- input space
- metric learning
- principal components
- high dimensionality
- nearest neighbor
- pattern recognition
- support vector
- website
- data sets