Kernel-based dimensionality reduction using Renyi's α-entropy measures of similarity.
Andrés Marino Álvarez-MezaJohn Aldo LeeMichel VerleysenGermán Castellanos-DomínguezPublished in: Neurocomputing (2017)
Keyphrases
- dimensionality reduction
- shannon entropy
- kernel pca
- euclidean distance
- similarity measure
- multidimensional scaling
- dimensionality reduction methods
- principal component analysis
- information theory
- mutual information
- pattern recognition
- high dimensionality
- high dimensional
- information theoretic
- kernel discriminant analysis
- linear discriminant analysis
- data representation
- kernel trick
- distance measure
- data points
- levenshtein distance
- feature selection
- fuzzy entropy
- similarity metric
- manifold learning
- edit distance
- principal components
- high dimensional data
- feature space
- machine learning
- similarity measurement
- structural similarity
- distance function
- nonlinear dimensionality reduction
- individual features
- support vector
- semi supervised dimensionality reduction
- feature extraction
- structure preserving
- co occurrence
- entropy measure
- online learning
- proximity measures
- metric learning