Hierarchical Clustering of High-Dimensional Data Without Global Dimensionality Reduction.
Ilari KampmanTapio ElomaaPublished in: ISMIS (2018)
Keyphrases
- dimensionality reduction
- low dimensional
- data representation
- high dimensional data
- principal component analysis
- structure preserving
- hierarchical clustering
- feature extraction
- pattern recognition
- high dimensional
- data sets
- hierarchical model
- manifold learning
- linear discriminant analysis
- unsupervised learning
- real time
- text categorization
- least squares
- hierarchical structure
- feature selection
- dimension reduction
- information systems
- computer vision
- neural network
- databases
- kernel learning
- linear dimensionality reduction
- pattern recognition and machine learning