Dimension Reduction for Clustering Time Series Using Global Characteristics.
Xiaozhe WangKate A. SmithRob J. HyndmanPublished in: International Conference on Computational Science (3) (2005)
Keyphrases
- dimension reduction
- multivariate time series
- cluster analysis
- high dimensional data analysis
- high dimensional data
- unsupervised learning
- high dimensionality
- principal component analysis
- clustering algorithm
- low dimensional
- high dimensional problems
- manifold learning
- clustering method
- high dimensional
- data mining and machine learning
- partial least squares
- feature space
- feature subspace
- feature extraction
- linear discriminant analysis
- singular value decomposition
- discriminative information
- k means
- variable selection
- data points
- feature selection
- generative topographic mapping
- document clustering
- dimensionality reduction
- nearest neighbor
- preprocessing
- spectral clustering
- random projections
- data clustering
- self organizing maps
- similarity search
- database
- sparse metric learning