Local Explanation of Dimensionality Reduction.
Avraam BardosIoannis MollasNick BassiliadesGrigorios TsoumakasPublished in: SETN (2022)
Keyphrases
- dimensionality reduction
- high dimensional data
- low dimensional
- principal component analysis
- feature extraction
- pattern recognition
- high dimensional
- high dimensionality
- data representation
- principal components
- dimensionality reduction methods
- lower dimensional
- data points
- intrinsic dimensionality
- manifold learning
- pattern recognition and machine learning
- structure preserving
- euclidean distance
- singular value decomposition
- dimension reduction
- counter intuitive
- feature selection
- diffusion maps
- random projections
- kernel learning
- graph embedding
- explanation based learning
- linear discriminant analysis
- linear dimensionality reduction
- feature space
- case study
- data mining
- causal explanation
- nonlinear dimensionality reduction
- preprocessing step
- pattern classification
- sparse representation
- input data
- learning algorithm