Z-Embedding: A Spectral Representation of Event Intervals for Efficient Clustering and Classification.
Zed LeeSarunas GirdzijauskasPanagiotis PapapetrouPublished in: ECML/PKDD (1) (2020)
Keyphrases
- classification accuracy
- unsupervised learning
- clustering algorithm
- machine learning
- feature representation
- unsupervised clustering
- supervised classification
- feature extraction
- unsupervised classification
- k means
- image classification
- pattern classification
- data clustering
- clustering method
- spectral features
- temporal relationships
- support vector machine
- support vector machine svm
- normalized cut
- data sets
- classification method
- clustering analysis
- vector space
- document clustering
- hyperspectral data
- hyperspectral images
- feature selection
- spectral decomposition
- classification algorithm
- hyperspectral imagery
- spectral clustering
- distance metric
- self organizing maps
- dimensionality reduction
- supervised learning
- data points
- feature vectors
- training set
- decision trees
- neural network