Dimensionality reduction and topographic mapping of binary tensors.
Jakub MazgutPeter TiñoMikael BodénHong YanPublished in: Pattern Anal. Appl. (2014)
Keyphrases
- dimensionality reduction
- principal component analysis
- data representation
- low dimensional
- pattern recognition
- high dimensionality
- high dimensional
- unsupervised learning
- high order
- dimensionality reduction methods
- data points
- structure preserving
- linear dimensionality reduction
- pattern recognition and machine learning
- high dimensional data
- tensor voting
- random projections
- manifold learning
- neural network
- feature selection
- euclidean distance
- feature extraction
- nonlinear dimensionality reduction
- ant based clustering
- anisotropic diffusion
- hamming distance
- linear discriminant analysis
- diffusion tensor
- multidimensional scaling
- machine learning
- data sets
- supervised dimensionality reduction