Dimensionality Reduction for Visualization of Time Series and Trajectories.
Pattreeya TanisaroGunther HeidemannPublished in: SCIA (2019)
Keyphrases
- dimensionality reduction
- trajectory data
- multidimensional scaling
- high dimensional
- low dimensional
- phase space
- feature extraction
- dynamic time warping
- high dimensional data
- principal component analysis
- pattern recognition and machine learning
- data analysis
- euclidean distance
- high dimensionality
- random projections
- multivariate time series
- data visualization
- non stationary
- dimensionality reduction methods
- data representation
- kernel pca
- pattern recognition
- feature selection
- chronic hepatitis
- data points
- kernel learning
- manifold learning
- interactive visualization
- structure preserving
- linear dimensionality reduction
- moving objects
- symbolic representation
- visualization tool
- autoregressive
- motion patterns
- principal components
- linear discriminant analysis
- feature space